Clement of Alexandria -- A Basic Stylometric Study

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Clement of Alexandria -- A Basic Stylometric Study

Post by Peter Kirby » Mon Jun 01, 2015 2:57 pm

This continues the series of "proving the obvious" (perhaps a misnomer--but what I'm primarily trying to do is to establish a baseline for using this stylometric technique; secondarily, this may firm up some of the 'foundational' beliefs about authorship accepted in patristic studies).

I started with the Protrepticus, which is the apology directed at Gentiles that is attributed to Clement. From this I derived a list of 22 'words' that performed well at distinguishing Clement from the other authors/controls when doing a 'leave-one-out' stylometric analysis (take extracts as the sample, leave that sample out and put the rest of the work as a candidate author).

Then I took samples from the 'Protrepticus' and the "Paedagogus', generally just over 3000 words in length. For the samples from the 'Protrepticus', one of the candidate author texts was the full text of the 'Paedagogus'. And, vice, versa, for the samples from the 'Paedagogus', the full text of the 'Protrepticus' was used as one of the candidate authors.

The two other candidate authors were Origen and Eusebius. Twenty-nine controls were used. This makes a small group of 3 candidates and a larger group of 32 candidates, including the controls as well.

Clement of Alexandria was selected as the best author 100% of the time when determining which of the three candidate authors were best.

10 out of 14 times, the sample from the 'Paedagogus' was matched with the text of the 'Protrepticus' (from 32 candidates, including controls). 6 out of 6 times, the sample from the 'Protrepticus' was matched with the text of the 'Paedagogus' (from 32 candidates, including controls). That makes for an accuracy rate of 80% total, which is considered fairly typical in stylometric studies. Since 80% of the time, the other work is selected as the best candidate author, it seems extremely likely that the same author wrote both works.

Direct quotations were removed from the text in a pre-processing step. This did appear to improve accuracy, perhaps suggesting that Clement makes genuine quotations.

Z-score-based (weighted average) scoring performed dramatically better than chi-square-based (Fisher's method) scoring. Chi-square-based (Fisher's method) selected Eusebius 5 times and Clement of Alexandria 15 times among three author candidates, which amounts to 75% accuracy picking from three, compared to 100% accuracy for the Z-score-based method. Chi-square-based (Fisher's method) scoring selected Strabo 11 times and Galen 9 times, always favoring a control over an author candidate (0% accuracy), when picking from 32 options. As a result, it takes on strictly secondary importance.

Given the texts used, the sample length used, and the particular words used, an author tends to have a Z-score-based P-value for his own text that is almost always greater than 0.05. This had already been observed previously. Thus, this statistic has been added to the printed results, using classifications of 'Bad' (less than 0.01), 'Poor' (between 0.01 and 0.05), 'Good' (between 0.05 and 0.1), and 'Excellent' (greater than 0.1). This statistic can provide an absolute (rather than relative) estimate of the 'fit' of the best candidate author to the test sample.

Given the fact that the 'Paedagogus' explicitly claims authorship of the 'Protrepticus', it is not surpising that the same author wrote both.
List of Controls Used:
(1) Josephus, (2) Acts, (3) Justin, (4) Theophilus of Antioch, (5) Irenaeus, (6) Mark, (7) John, (8) 1 Cor, (9) Hebrews, (10) Revelation, (11) Letter of Aristeas, (12) 1 Maccabees, (13) 2 Maccabees, (14) Polybius, (15) Diodorus Siculus, (16) Dionysius Halicarnassus, (17) Strabo, (18) Plutarch, (19) Arrian, (20) Herodian, (21) Herodotus, (22) Thucydides, (23) Xenophon, (24) Epictetus, (25) Galen, (26) Basil, (27) Philostratus, (28) Athanasius, (29) John Chrysostom
Further analysis, performed with the 'Stromata' (also with the quotations removed), suggests that the frequency of 'te' and the frequency of 'kata' may not be invariant across Clement's works. Of the three author candidates, 'Clement' (the author of the Protrepticus and Paedagogus) was selected 13 out of 16 times (for 81.25% accuracy). Of the 32 candidates, 'Clement' was selected 9 out of 16 times (for 56.25% accuracy). This is when including these two words.

When removing these two words from the list, the situation improved. With twenty words now, 16 out of 16 samples (for 100% accuracy) from the 'Stromata' are identified with the author designated as 'Clement' (the author of the Protrepticus and Paedagogus), while 13 out of 16 samples are correctly identified with this same 'Clement' as the best author when pitted against 31 other candidates, including the controls (for 81.25% accuracy).

I was able to get two samples from "Who Is the Rich Man Who Will Be Saved?" I used the 20-word list again, with the text representing the candidate 'Clement' being an amalgam of the 'Protrepticus', 'Paedagogus', and 'Stromata'. Once again, the quotes were stripped out of Clement's text. Both results indicated 'Clement' as the author, whether compared to the other author candidates or when including the controls.

I was able to get two samples from "Excerpts from Theodotus." I used the 20-word list again, with the text representing the candidate 'Clement' being an amalgam of the 'Protrepticus', 'Paedagogus', and 'Stromata'. Once again, the quotes were stripped out of Clement's text. Both results indicated 'Clement' as the author, whether compared to the other author candidates or when including the controls.

Same thing again... This time, with the 'fragments' of Clement that are contained in the TLG (4365 words, from various sources, mostly church fathers and catenae). I didn't do an excellent job of separating the introductory words or the paraphrases from the actual, explicit quotes (although I did try). In any case, it seems to identify 'Clement' as the most likely author when a large sample is taken of these fragments. This cannot be said to authenticate all the fragments, however; it merely suggests the probability that, at least, many or most of them were from Clement.

The so-called 'Letter to Theodore' could neither be authenticated nor disproven as authentic. As shown from the small frequencies of the 'words' measured, it is very difficult to use Clement's habits of style to identify a text only 749 words long. This is even though I didn't cull out the incipit and the long quote of the 'secret gospel.' (If using a 'z-scored p-value < 0.1' test, only 10 of 32 candidates are excluded. If using a 'z-scored p-value < 0.05' test, only 3 of 32 candidates are excluded.)

With this method, at least, there is a huge difference between a 750-word sample and a 3000-word sample. The most that can be said is that this doesn't disprove Clementine authorship of the 'Letter to Theodore'. It's possible that more-advanced stylometric techniques could provide useful information. Some studies have had good results with English texts of 250 words.

The 'Hymnus Christi servatoris' and the 'Eclogae propheticae' were also too short to be tested with this method.

There are no other works attributed to Clement of Alexandria in the TLG.
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Peter Kirby » Mon Jun 01, 2015 2:58 pm

Here are the six results using samples from the 'Protrepticus'.

Sample 1 - 'Protrepticus'
testsize: 3488
$VAR1 = 35; $VAR2 = 19; $VAR3 = 71; $VAR4 = 205; $VAR5 = 12; $VAR6 = 100; $VAR7 = 26; $VAR8 = 11; $VAR9 = 22; $VAR10 = 25; $VAR11 = 22; $VAR12 = 14; $VAR13 = 7; $VAR14 = 4; $VAR15 = 12; $VAR16 = 5; $VAR17 = 7; $VAR18 = 5; $VAR19 = 4; $VAR20 = 4; $VAR21 = 11; $VAR22 = 14;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.195551922755703'; $VAR2 = '0.00202280202113641'; $VAR3 = '0.0423876169133424';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0151281486863678'; $VAR2 = '0.0145042281588148'; $VAR3 = '0.0675915655426189'; $VAR4 = '0.10823097259525'; $VAR5 = '0.0542476670111339'; $VAR6 = '3.91843352799618e-11'; $VAR7 = '9.14696348750138e-08'; $VAR8 = '0'; $VAR9 = '3.79432951525788e-263'; $VAR10 = '1.22150091149652e-77'; $VAR11 = '0.0252284045646925'; $VAR12 = '3.65771346263625e-14'; $VAR13 = '0.000246255687234505'; $VAR14 = '0.0101186704442395'; $VAR15 = '0.0147908801718385'; $VAR16 = '0.0158742264951668'; $VAR17 = '0.0419358671308489'; $VAR18 = '0.000278580342514353'; $VAR19 = '0.00338964000352063'; $VAR20 = '1.78143710934996e-06'; $VAR21 = '8.41378941980205e-06'; $VAR22 = '0.000465591994604541'; $VAR23 = '0.0275793437846606'; $VAR24 = '9.65339935045629e-06'; $VAR25 = '0.00575164447369743'; $VAR26 = '0.0190793430049276'; $VAR27 = '3.18806758272083e-05'; $VAR28 = '0.0212428349408546'; $VAR29 = '0.0206026284188241';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.814927548124124'; $VAR2 = '0.00842966445021641'; $VAR3 = '0.17664278742566';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.643722624770518'; $VAR3 = 4; $VAR4 = '0.356277375229482';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.995559285217461'; $VAR2 = '0.108029521304611'; $VAR3 = '0.0624956100367143';

Control Chi-Square-Based P-Values
$VAR1 = '3.89062703020665e-05'; $VAR2 = '0.000453085062541578'; $VAR3 = '0.700954948159321'; $VAR4 = '0.99408250472263'; $VAR5 = '0.999332763583343'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '2.54746691859661e-05'; $VAR12 = 0; $VAR13 = 0; $VAR14 = '3.31522753727369e-07'; $VAR15 = '0.427464360992527'; $VAR16 = '0.233321503917167'; $VAR17 = '0.793559857009335'; $VAR18 = '8.47050414335915e-12'; $VAR19 = '3.66007564497292e-13'; $VAR20 = '3.97556652073843e-14'; $VAR21 = 0; $VAR22 = 0; $VAR23 = '0.984493474576463'; $VAR24 = '9.03633828987819e-13'; $VAR25 = '0.999961555453993'; $VAR26 = '1.32581965682582e-09'; $VAR27 = 0; $VAR28 = '0.749871738608557'; $VAR29 = '0.0306898126726929';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.853762618795164'; $VAR2 = '0.09264296801377'; $VAR3 = '0.0535944131910657';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.498896962099616'; $VAR3 = 25; $VAR4 = '0.501103037900384';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.7 Test, Chi-Square-Based Method
0.230769230769231
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.7 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.7 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.7 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 2 - 'Protrepticus'
testsize: 3358
$VAR1 = 48; $VAR2 = 23; $VAR3 = 56; $VAR4 = 213; $VAR5 = 17; $VAR6 = 141; $VAR7 = 34; $VAR8 = 15; $VAR9 = 21; $VAR10 = 9; $VAR11 = 36; $VAR12 = 9; $VAR13 = 10; $VAR14 = 11; $VAR15 = 12; $VAR16 = 2; $VAR17 = 0; $VAR18 = 5; $VAR19 = 8; $VAR20 = 8; $VAR21 = 7; $VAR22 = 25;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0983506865468302'; $VAR2 = '0.00567109389787289'; $VAR3 = '0.0817711666373299';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.0372455400547908'; $VAR2 = '0.00589332052878464'; $VAR3 = '0.0408691380122363'; $VAR4 = '0.0383360758610487'; $VAR5 = '0.0060138577261958'; $VAR6 = '6.51336980537479e-14'; $VAR7 = '8.70206837740581e-13'; $VAR8 = '1.53258497906415e-23'; $VAR9 = '0'; $VAR10 = '6.48984227753807e-74'; $VAR11 = '0.00261167512997654'; $VAR12 = '3.43934610828377e-20'; $VAR13 = '0.00204033338640978'; $VAR14 = '0.0220894974368376'; $VAR15 = '0.0206442236226216'; $VAR16 = '0.0372029704575276'; $VAR17 = '0.0657865549817408'; $VAR18 = '0.0236105699002196'; $VAR19 = '0.0117761733612931'; $VAR20 = '0.00200020409940319'; $VAR21 = '0.0021222451182589'; $VAR22 = '0.0195144770101537'; $VAR23 = '0.0809187710190425'; $VAR24 = '4.25518914319368e-14'; $VAR25 = '0.000699200138504399'; $VAR26 = '0.0125291341886085'; $VAR27 = '0.0132372999665358'; $VAR28 = '0.00854336260042781'; $VAR29 = '0.0115133940345381';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.529356405027611'; $VAR2 = '0.0305237307817123'; $VAR3 = '0.440119864190677';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.548619312415173'; $VAR3 = 23; $VAR4 = '0.451380687584827';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0983 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0983 Test, Z-Score-Based Method
0.00495049504950495
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.995073891625616

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0983 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0983 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.0308395015917966'; $VAR2 = '4.27008831394496e-11'; $VAR3 = '0.376839561067125';

Control Chi-Square-Based P-Values
$VAR1 = '0.0268705287362732'; $VAR2 = '8.78103076452334e-23'; $VAR3 = '8.62302348178258e-06'; $VAR4 = '0.000279445561044455'; $VAR5 = '5.55241999143426e-05'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '8.25864005413125e-37'; $VAR12 = 0; $VAR13 = '2.21512349537211e-09'; $VAR14 = '0.0426011702299659'; $VAR15 = '0.00757888612000238'; $VAR16 = '0.450364948441279'; $VAR17 = '0.989275442076037'; $VAR18 = '0.180185818208162'; $VAR19 = '4.69522145964403e-08'; $VAR20 = 0; $VAR21 = 0; $VAR22 = '2.1955394498196e-21'; $VAR23 = '0.982278045715435'; $VAR24 = '4.41863218446475e-11'; $VAR25 = '2.08171392882311e-25'; $VAR26 = '1.33536531974071e-23'; $VAR27 = '1.16013770154567e-23'; $VAR28 = '1.31805969390797e-06'; $VAR29 = '3.17918500658863e-18';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.0756465180905496'; $VAR2 = '1.04741418056836e-10'; $VAR3 = '0.924353481804709';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 3; $VAR2 = '0.275847611804344'; $VAR3 = 17; $VAR4 = '0.724152388195656';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.3 Test, Chi-Square-Based Method
0.625
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.3 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.3 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.3 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 3 - Protrepticus
testsize: 3311
$VAR1 = 46; $VAR2 = 34; $VAR3 = 91; $VAR4 = 161; $VAR5 = 14; $VAR6 = 100; $VAR7 = 29; $VAR8 = 22; $VAR9 = 23; $VAR10 = 9; $VAR11 = 64; $VAR12 = 12; $VAR13 = 8; $VAR14 = 14; $VAR15 = 11; $VAR16 = 1; $VAR17 = 3; $VAR18 = 4; $VAR19 = 7; $VAR20 = 5; $VAR21 = 8; $VAR22 = 12;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.134879823779009'; $VAR2 = '0.0161237284681351'; $VAR3 = '0.0460218603567077';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0195775874340186'; $VAR2 = '0.00479033439248452'; $VAR3 = '0.0452430380881673'; $VAR4 = '0.0416272456994701'; $VAR5 = '0.00198232579760425'; $VAR6 = '8.86787467271368e-12'; $VAR7 = '5.15217714343172e-08'; $VAR8 = '1.76862430799916e-12'; $VAR9 = '3.2770089565752e-278'; $VAR10 = '1.00450821376516e-234'; $VAR11 = '3.97263478087261e-06'; $VAR12 = '7.16099645215798e-20'; $VAR13 = '2.18330878194877e-05'; $VAR14 = '0.0037496350065064'; $VAR15 = '0.00568835757385869'; $VAR16 = '0.0239461076965492'; $VAR17 = '0.0464773377255677'; $VAR18 = '8.76509686532967e-05'; $VAR19 = '0.00337676511826499'; $VAR20 = '0.00145366407335527'; $VAR21 = '0.000310874529702696'; $VAR22 = '0.0118790604758047'; $VAR23 = '0.0208955419281204'; $VAR24 = '0.000858141426789473'; $VAR25 = '0.0144703444439138'; $VAR26 = '0.0521270161754494'; $VAR27 = '0.0103172704762633'; $VAR28 = '0.0311503951611195'; $VAR29 = '0.018989628792688';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.684580846686029'; $VAR2 = '0.0818357807505479'; $VAR3 = '0.233583372563423';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.721256098503436'; $VAR3 = 26; $VAR4 = '0.278743901496564';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.00483091787439614
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.995192307692308

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.000598481053972707'; $VAR2 = '0.000893948637798419'; $VAR3 = '0.0286232139098417';

Control Chi-Square-Based P-Values
$VAR1 = '1.57244413537657e-06'; $VAR2 = '2.15471995623262e-23'; $VAR3 = '0.0173324093985278'; $VAR4 = '0.0215001428096618'; $VAR5 = '9.10824650441725e-10'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = 0; $VAR12 = 0; $VAR13 = 0; $VAR14 = '3.2806842202086e-15'; $VAR15 = '7.50840964840216e-07'; $VAR16 = '0.050412385315852'; $VAR17 = '0.000768152744589035'; $VAR18 = '1.19682511961312e-12'; $VAR19 = '6.39622299884579e-12'; $VAR20 = 0; $VAR21 = 0; $VAR22 = '3.27709713780523e-22'; $VAR23 = '0.000998983907109171'; $VAR24 = '2.03141168731671e-07'; $VAR25 = '0.323231126328478'; $VAR26 = '0.000494031806895481'; $VAR27 = '4.46487464860337e-27'; $VAR28 = '0.0556417479569816'; $VAR29 = '6.40580802287918e-05';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.0198727632020674'; $VAR2 = '0.0296838629658423'; $VAR3 = '0.95044337383209';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 3; $VAR2 = '0.0813496115763542'; $VAR3 = 25; $VAR4 = '0.918650388423646';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0286 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0286 Test, Chi-Square-Based Method
0.0234741784037559
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
0.977064220183486

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0286 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0286 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 4 - 'Protrepticus'
testsize: 3303
$VAR1 = 38; $VAR2 = 32; $VAR3 = 50; $VAR4 = 185; $VAR5 = 19; $VAR6 = 76; $VAR7 = 33; $VAR8 = 21; $VAR9 = 30; $VAR10 = 14; $VAR11 = 19; $VAR12 = 9; $VAR13 = 8; $VAR14 = 13; $VAR15 = 11; $VAR16 = 1; $VAR17 = 3; $VAR18 = 10; $VAR19 = 14; $VAR20 = 12; $VAR21 = 19; $VAR22 = 8;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.115991298417157'; $VAR2 = '0.0099704378191568'; $VAR3 = '0.0761093456396583';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0211599557232139'; $VAR2 = '0.00352258019650652'; $VAR3 = '0.036712175105279'; $VAR4 = '0.0449195740163874'; $VAR5 = '0.00398799708901976'; $VAR6 = '6.93513193576349e-12'; $VAR7 = '1.91581453215373e-08'; $VAR8 = '1.98379542989606e-17'; $VAR9 = '1.44640938861734e-249'; $VAR10 = '1.07117252049979e-235'; $VAR11 = '0.000223502731034483'; $VAR12 = '1.30155809684698e-20'; $VAR13 = '0.000768846159699791'; $VAR14 = '0.0193643632074808'; $VAR15 = '0.0110992470988959'; $VAR16 = '0.0304196253187619'; $VAR17 = '0.0922031592678244'; $VAR18 = '3.63096846856778e-06'; $VAR19 = '0.00219206190234858'; $VAR20 = '0.000998165189998664'; $VAR21 = '0.000167301993765545'; $VAR22 = '0.00659837873037905'; $VAR23 = '0.0336559174274162'; $VAR24 = '0.00434925705679446'; $VAR25 = '0.0210389598212983'; $VAR26 = '0.0492577470607874'; $VAR27 = '0.0111052524933639'; $VAR28 = '0.035593146904141'; $VAR29 = '0.0597516172959452';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.574012359118018'; $VAR2 = '0.0493412403526226'; $VAR3 = '0.37664640052936';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.557129616738708'; $VAR3 = 17; $VAR4 = '0.442870383261292';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.00483091787439614
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.995192307692308

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.27845630217532'; $VAR2 = '9.62599730403314e-06'; $VAR3 = '0.175830392473127';

Control Chi-Square-Based P-Values
$VAR1 = '4.85478082279241e-11'; $VAR2 = '1.30759804823572e-29'; $VAR3 = '0.00990445726394746'; $VAR4 = '0.00498284332204067'; $VAR5 = '7.94260972743977e-06'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = 0; $VAR12 = 0; $VAR13 = '9.38105081344272e-16'; $VAR14 = '0.0180557066690292'; $VAR15 = '0.411927021452741'; $VAR16 = '0.248434658456575'; $VAR17 = '0.998063512045373'; $VAR18 = '7.65267154278231e-21'; $VAR19 = '7.26500694871303e-15'; $VAR20 = 0; $VAR21 = 0; $VAR22 = 0; $VAR23 = '0.0489071021941194'; $VAR24 = '0.22016162252971'; $VAR25 = '0.967883836661252'; $VAR26 = '5.39351455269254e-05'; $VAR27 = 0; $VAR28 = '0.18036388189407'; $VAR29 = '0.899754200346927';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.612939813775101'; $VAR2 = '2.11888075394281e-05'; $VAR3 = '0.38703899741736';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.218137077915485'; $VAR3 = 17; $VAR4 = '0.781862922084515';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Chi-Square-Based Method
0.785714285714286
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 5 - 'Protrepticus'
testsize: 3201
$VAR1 = 41; $VAR2 = 42; $VAR3 = 62; $VAR4 = 141; $VAR5 = 7; $VAR6 = 93; $VAR7 = 19; $VAR8 = 16; $VAR9 = 37; $VAR10 = 24; $VAR11 = 14; $VAR12 = 20; $VAR13 = 15; $VAR14 = 8; $VAR15 = 16; $VAR16 = 3; $VAR17 = 1; $VAR18 = 1; $VAR19 = 8; $VAR20 = 8; $VAR21 = 13; $VAR22 = 19;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.145813737626526'; $VAR2 = '0.00162355203946694'; $VAR3 = '0.0172428115550228';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.00568610870870682'; $VAR2 = '0.00420524345591772'; $VAR3 = '0.0636681899364524'; $VAR4 = '0.0687199220135862'; $VAR5 = '0.00499044060379017'; $VAR6 = '3.59851084147939e-11'; $VAR7 = '8.49382484018295e-08'; $VAR8 = '1.63246203744396e-08'; $VAR9 = '2.00838514782523e-249'; $VAR10 = '3.14110683854663e-29'; $VAR11 = '0.00821187209747016'; $VAR12 = '7.73678443003861e-16'; $VAR13 = '0.00020463845320472'; $VAR14 = '0.00826982796737257'; $VAR15 = '0.0101336558220085'; $VAR16 = '0.0189383188277388'; $VAR17 = '0.0550258676939474'; $VAR18 = '1.19196120115251e-10'; $VAR19 = '0.000210988993344849'; $VAR20 = '1.16131958129854e-06'; $VAR21 = '9.25125953573196e-07'; $VAR22 = '0.000199290044746444'; $VAR23 = '0.0160204237177689'; $VAR24 = '0.00164786952435545'; $VAR25 = '0.0477200799787901'; $VAR26 = '0.060036558915104'; $VAR27 = '4.18892207539714e-06'; $VAR28 = '0.03297701357656'; $VAR29 = '0.00739713511195794';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.885436288570352'; $VAR2 = '0.00985882342450097'; $VAR3 = '0.104704888005147';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.679677668628474'; $VAR3 = 4; $VAR4 = '0.320322331371526';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.433065635619351'; $VAR2 = '4.78445073306331e-18'; $VAR3 = '5.92712214183332e-08';

Control Chi-Square-Based P-Values
$VAR1 = '3.30209867159928e-19'; $VAR2 = '8.42227473739776e-12'; $VAR3 = '0.0953013119465102'; $VAR4 = '0.454654623674323'; $VAR5 = '1.42835659114415e-27'; $VAR6 = 0; $VAR7 = 0; $VAR8 = '9.01478978903434e-19'; $VAR9 = 0; $VAR10 = 0; $VAR11 = '3.28162795333452e-14'; $VAR12 = 0; $VAR13 = 0; $VAR14 = '3.55836984097089e-07'; $VAR15 = '2.70340065213924e-09'; $VAR16 = '0.015141539769623'; $VAR17 = '0.798825654145153'; $VAR18 = '2.69533213777119e-33'; $VAR19 = '9.41441075636549e-56'; $VAR20 = '1.2703375953926e-17'; $VAR21 = 0; $VAR22 = 0; $VAR23 = '0.000115834009729692'; $VAR24 = '0.00824484099981705'; $VAR25 = '0.957825295476479'; $VAR26 = '0.0202419698776687'; $VAR27 = '6.90906016726012e-27'; $VAR28 = '0.0743978923552599'; $VAR29 = '7.01152860498833e-07';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.999999863135727'; $VAR2 = '1.10478636140234e-17'; $VAR3 = '1.36864272828883e-07';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.311358443669019'; $VAR3 = 25; $VAR4 = '0.688641556330981';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.4 Test, Chi-Square-Based Method
0.428571428571429
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.4 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.4 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.4 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 6 - 'Protrepticus'
testsize: 3258
$VAR1 = 36; $VAR2 = 26; $VAR3 = 65; $VAR4 = 167; $VAR5 = 10; $VAR6 = 68; $VAR7 = 29; $VAR8 = 18; $VAR9 = 26; $VAR10 = 23; $VAR11 = 24; $VAR12 = 6; $VAR13 = 4; $VAR14 = 15; $VAR15 = 17; $VAR16 = 7; $VAR17 = 5; $VAR18 = 1; $VAR19 = 5; $VAR20 = 5; $VAR21 = 19; $VAR22 = 14;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.130381415095656'; $VAR2 = '0.00537140215066178'; $VAR3 = '0.0435828930679954';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.014961711926187'; $VAR2 = '0.00112887461153307'; $VAR3 = '0.0655521361056134'; $VAR4 = '0.0775776437658759'; $VAR5 = '0.00373212202279496'; $VAR6 = '1.73198179976009e-08'; $VAR7 = '3.50710185718358e-06'; $VAR8 = '2.33863512593781e-14'; $VAR9 = '4.03703779691279e-194'; $VAR10 = '1.6201923372722e-28'; $VAR11 = '0.000901072205591044'; $VAR12 = '1.70055409798277e-18'; $VAR13 = '0.000331919153937235'; $VAR14 = '0.00205035893111265'; $VAR15 = '0.00774873603284791'; $VAR16 = '0.00764260621185638'; $VAR17 = '0.0267102004586712'; $VAR18 = '3.71621210570635e-06'; $VAR19 = '0.000544583790495605'; $VAR20 = '4.16212646089275e-06'; $VAR21 = '5.30174785856415e-07'; $VAR22 = '0.000186230817509624'; $VAR23 = '0.014180043468815'; $VAR24 = '0.00382939957365308'; $VAR25 = '0.0253112264450761'; $VAR26 = '0.0970015015014463'; $VAR27 = '1.31915371124249e-05'; $VAR28 = '0.0387486504738775'; $VAR29 = '0.0418225288387112';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.727024276799878'; $VAR2 = '0.0299516596067095'; $VAR3 = '0.243024063593412';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.573400223054917'; $VAR3 = 26; $VAR4 = '0.426599776945083';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.677051884605904'; $VAR2 = '3.92376945929141e-06'; $VAR3 = '0.00564630200176728';

Control Chi-Square-Based P-Values
$VAR1 = '2.94692070723635e-08'; $VAR2 = '1.19473373209663e-32'; $VAR3 = '0.259980249039108'; $VAR4 = '0.752196456632162'; $VAR5 = '7.25368251095608e-21'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = 0; $VAR12 = 0; $VAR13 = '4.93684717011403e-32'; $VAR14 = '2.48788244710675e-16'; $VAR15 = '7.87244398120831e-05'; $VAR16 = '4.1280921058515e-06'; $VAR17 = '0.0744232730113468'; $VAR18 = '2.61344526105859e-45'; $VAR19 = '1.53691166337437e-28'; $VAR20 = '2.56379594938797e-15'; $VAR21 = 0; $VAR22 = 0; $VAR23 = '8.52947446314246e-05'; $VAR24 = '0.947218751667666'; $VAR25 = '0.996299064480604'; $VAR26 = '0.876735479416249'; $VAR27 = '4.56291013339251e-43'; $VAR28 = '0.84975354553577'; $VAR29 = '0.810362426145468';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.991723731792618'; $VAR2 = '5.74741076620356e-06'; $VAR3 = '0.0082705207966154';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.404608420591933'; $VAR3 = 25; $VAR4 = '0.595391579408067';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.6 Test, Chi-Square-Based Method
0.214285714285714
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.6 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.6 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.6 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Peter Kirby
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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Peter Kirby » Mon Jun 01, 2015 3:00 pm

Sample 1 - 'Paedagogus'
testsize: 3857
$VAR1 = 77; $VAR2 = 19; $VAR3 = 95; $VAR4 = 210; $VAR5 = 19; $VAR6 = 118; $VAR7 = 38; $VAR8 = 20; $VAR9 = 41; $VAR10 = 43; $VAR11 = 36; $VAR12 = 12; $VAR13 = 15; $VAR14 = 24; $VAR15 = 20; $VAR16 = 4; $VAR17 = 7; $VAR18 = 2; $VAR19 = 6; $VAR20 = 1; $VAR21 = 15; $VAR22 = 15;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0852483734152764'; $VAR2 = '0.000160930563111951'; $VAR3 = '0.0325961587311756';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.0249234953669962'; $VAR2 = '0.000195880348978756'; $VAR3 = '0.0396783882725832'; $VAR4 = '0.0445324405995523'; $VAR5 = '0.0211284434118522'; $VAR6 = '6.21413843361468e-35'; $VAR7 = '1.28302525981251e-07'; $VAR8 = '0'; $VAR9 = '9.99298550812784e-231'; $VAR10 = '5.24185803263132e-92'; $VAR11 = '0.00325588817837839'; $VAR12 = '4.36066686647798e-25'; $VAR13 = '0.00328305664583042'; $VAR14 = '0.00189549673804374'; $VAR15 = '0.0138509260263236'; $VAR16 = '0.00555241339337605'; $VAR17 = '0.0357386350201838'; $VAR18 = '2.36065062791201e-06'; $VAR19 = '0.000161150840464078'; $VAR20 = '2.41017227271058e-10'; $VAR21 = '3.03168233851288e-09'; $VAR22 = '2.22564460118468e-05'; $VAR23 = '0.0349182549596931'; $VAR24 = '2.34117801481799e-11'; $VAR25 = '0.00893575349628543'; $VAR26 = '0.040148834546582'; $VAR27 = '7.54742006584651e-10'; $VAR28 = '0.0134975200308637'; $VAR29 = '0.00597770143711143';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.722410399127796'; $VAR2 = '0.00136375519757111'; $VAR3 = '0.276225845674632';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.656864221899055'; $VAR3 = 4; $VAR4 = '0.343135778100945';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0852 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0852 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0852 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0852 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '3.71614872878953e-06'; $VAR2 = '1.02542881024581e-11'; $VAR3 = '0.000373544114014811';

Control Chi-Square-Based P-Values
$VAR1 = '2.05386627336487e-08'; $VAR2 = 0; $VAR3 = '0.00014856703574615'; $VAR4 = '2.63166196114152e-05'; $VAR5 = '0.0154583152903057'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = 0; $VAR12 = 0; $VAR13 = '2.27205362724632e-31'; $VAR14 = '1.01545252903391e-17'; $VAR15 = '2.75028448085723e-06'; $VAR16 = '5.88736864506297e-09'; $VAR17 = '0.0264324442255359'; $VAR18 = 0; $VAR19 = 0; $VAR20 = '2.65977745406887e-18'; $VAR21 = '6.98058853489902e-31'; $VAR22 = '8.94471593407725e-13'; $VAR23 = '0.021806606945393'; $VAR24 = '3.45452732527367e-26'; $VAR25 = '0.354568084063454'; $VAR26 = '6.08579217220451e-07'; $VAR27 = '3.65013440687816e-22'; $VAR28 = '1.65048432065486e-10'; $VAR29 = '1.06876450829892e-11';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.00985035794853048'; $VAR2 = '2.71809380324429e-08'; $VAR3 = '0.990149614870531';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 3; $VAR2 = '0.00105240998620776'; $VAR3 = 25; $VAR4 = '0.998947590013792';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0003 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0003 Test, Chi-Square-Based Method
0.167630057803468
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
0.856435643564356

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0003 Test, Chi-Square-Based Method
1
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
0.5

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0003 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 2 - 'Paedagogus'
testsize: 3164
$VAR1 = 49; $VAR2 = 20; $VAR3 = 72; $VAR4 = 149; $VAR5 = 4; $VAR6 = 90; $VAR7 = 26; $VAR8 = 23; $VAR9 = 32; $VAR10 = 29; $VAR11 = 29; $VAR12 = 10; $VAR13 = 20; $VAR14 = 16; $VAR15 = 15; $VAR16 = 4; $VAR17 = 11; $VAR18 = 4; $VAR19 = 7; $VAR20 = 2; $VAR21 = 8; $VAR22 = 10;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.110425411491188'; $VAR2 = '0.0168100053076322'; $VAR3 = '0.0247702586232463';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.00474763483993693'; $VAR2 = '0.00205132964856352'; $VAR3 = '0.0603679510560854'; $VAR4 = '0.115245095120927'; $VAR5 = '0.000694290642582177'; $VAR6 = '1.89814298106183e-13'; $VAR7 = '4.25883093969453e-07'; $VAR8 = '3.02309590093737e-12'; $VAR9 = '5.94685146069209e-171'; $VAR10 = '6.63017846494759e-30'; $VAR11 = '0.00237576102457757'; $VAR12 = '4.72264622817059e-17'; $VAR13 = '0.000499514393659058'; $VAR14 = '0.00384951477041616'; $VAR15 = '0.0118689749408256'; $VAR16 = '0.00618182140145521'; $VAR17 = '0.0782610119434397'; $VAR18 = '6.41180181792071e-08'; $VAR19 = '0.0011812106196608'; $VAR20 = '7.10699710120488e-08'; $VAR21 = '1.66161477647737e-07'; $VAR22 = '1.20669162703879e-05'; $VAR23 = '0.0276372342739506'; $VAR24 = '0.0041331159120497'; $VAR25 = '0.0622712915143119'; $VAR26 = '0.143895671266581'; $VAR27 = '4.39479139337087e-07'; $VAR28 = '0.0758626798923688'; $VAR29 = '0.0155745148540225';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.726455845708231'; $VAR2 = '0.11058801101312'; $VAR3 = '0.16295614327865';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.434196843980741'; $VAR3 = 26; $VAR4 = '0.565803156019259';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.00327647662238583'; $VAR2 = '2.46052500162838e-12'; $VAR3 = '2.05051497438385e-05';

Control Chi-Square-Based P-Values
$VAR1 = '5.52824160226299e-23'; $VAR2 = '4.07275217113349e-28'; $VAR3 = '0.0403893970201034'; $VAR4 = '0.730830401110891'; $VAR5 = 0; $VAR6 = '1.06294609948117e-49'; $VAR7 = 0; $VAR8 = '3.31385038025241e-50'; $VAR9 = 0; $VAR10 = 0; $VAR11 = 0; $VAR12 = 0; $VAR13 = 0; $VAR14 = '1.18608088603118e-15'; $VAR15 = '1.14134031514335e-07'; $VAR16 = '7.49731235206691e-06'; $VAR17 = '0.831254599348257'; $VAR18 = 0; $VAR19 = '1.49137796266636e-41'; $VAR20 = '2.04862929364565e-18'; $VAR21 = 0; $VAR22 = '1.09692800593617e-13'; $VAR23 = '0.0375835772273259'; $VAR24 = '1.81928872745039e-06'; $VAR25 = '0.911662490675726'; $VAR26 = '0.410633740132195'; $VAR27 = '1.82379962590442e-30'; $VAR28 = '0.407803038003259'; $VAR29 = '3.70083469305657e-07';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.993780629191706'; $VAR2 = '7.46296209639867e-10'; $VAR3 = '0.00621937006199775';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.00358108763479768'; $VAR3 = 25; $VAR4 = '0.996418912365202';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0032 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0032 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0032 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0032 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 3 - 'Paedagogus'
testsize: 3387
$VAR1 = 76; $VAR2 = 19; $VAR3 = 82; $VAR4 = 183; $VAR5 = 12; $VAR6 = 109; $VAR7 = 27; $VAR8 = 25; $VAR9 = 42; $VAR10 = 31; $VAR11 = 19; $VAR12 = 10; $VAR13 = 18; $VAR14 = 17; $VAR15 = 15; $VAR16 = 2; $VAR17 = 11; $VAR18 = 1; $VAR19 = 6; $VAR20 = 4; $VAR21 = 11; $VAR22 = 14;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0993610612503758'; $VAR2 = '0.0164009631898812'; $VAR3 = '0.0418761643891588';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.00804200125540388'; $VAR2 = '0.00230028386038919'; $VAR3 = '0.0596038839942508'; $VAR4 = '0.12703175759257'; $VAR5 = '0.00878611042637326'; $VAR6 = '3.33668961706171e-11'; $VAR7 = '2.49995787447009e-10'; $VAR8 = '6.85095404810077e-15'; $VAR9 = '1.19631041248422e-180'; $VAR10 = '2.73684326428732e-76'; $VAR11 = '0.00385205884466367'; $VAR12 = '7.9558942287401e-17'; $VAR13 = '0.000120844332547725'; $VAR14 = '0.003762303129174'; $VAR15 = '0.0110166841407004'; $VAR16 = '0.0087658151271015'; $VAR17 = '0.067515789844668'; $VAR18 = '2.29330354211417e-05'; $VAR19 = '0.000104489814535931'; $VAR20 = '4.88264691388305e-08'; $VAR21 = '5.20662353234925e-07'; $VAR22 = '0.000222366324519673'; $VAR23 = '0.0337163706373772'; $VAR24 = '1.58624555132982e-05'; $VAR25 = '0.0237363157163827'; $VAR26 = '0.0694227160566823'; $VAR27 = '7.88995024173805e-05'; $VAR28 = '0.044075087678035'; $VAR29 = '0.0185729613260712';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.630310852898068'; $VAR2 = '0.104041814433868'; $VAR3 = '0.265647332668063';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.438887866488844'; $VAR3 = 4; $VAR4 = '0.561112133511156';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0993 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0993 Test, Z-Score-Based Method
0.0050251256281407
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.995

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0993 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0993 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '1.70296095124016e-08'; $VAR2 = '5.12616883622468e-08'; $VAR3 = '1.34354117511925e-07';

Control Chi-Square-Based P-Values
$VAR1 = '5.48095249661582e-15'; $VAR2 = '6.19226118929047e-49'; $VAR3 = '0.00854358241531979'; $VAR4 = '0.374602373569949'; $VAR5 = '1.89398649633893e-16'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '1.91494316676167e-39'; $VAR12 = 0; $VAR13 = 0; $VAR14 = '7.86140523954686e-17'; $VAR15 = '1.74556844577035e-07'; $VAR16 = '9.66420613880301e-05'; $VAR17 = '0.254644378528444'; $VAR18 = '5.63572987341047e-45'; $VAR19 = 0; $VAR20 = '1.64026876737529e-27'; $VAR21 = 0; $VAR22 = '2.1656004379135e-12'; $VAR23 = '0.00813715998014923'; $VAR24 = 0; $VAR25 = '0.487492234167555'; $VAR26 = '5.33987439936272e-07'; $VAR27 = '7.35935599251395e-25'; $VAR28 = '0.241572572262219'; $VAR29 = '3.07167784810041e-10';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.084036490437819'; $VAR2 = '0.252962487527577'; $VAR3 = '0.663001022034604';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 3; $VAR2 = '2.75602504136333e-07'; $VAR3 = 25; $VAR4 = '0.999999724397496';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0 Test, Chi-Square-Based Method
0.913705583756345
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
0.522546419098143

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0 Test, Chi-Square-Based Method
1
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
0.5

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0 Test, Chi-Square-Based Method
1
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
0.5
Sample 4 - 'Paedagogus'
testsize: 3196
$VAR1 = 67; $VAR2 = 5; $VAR3 = 96; $VAR4 = 196; $VAR5 = 10; $VAR6 = 96; $VAR7 = 31; $VAR8 = 20; $VAR9 = 41; $VAR10 = 27; $VAR11 = 12; $VAR12 = 15; $VAR13 = 9; $VAR14 = 27; $VAR15 = 12; $VAR16 = 2; $VAR17 = 15; $VAR18 = 0; $VAR19 = 11; $VAR20 = 5; $VAR21 = 13; $VAR22 = 19;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0575194559078539'; $VAR2 = '0.0169373548061582'; $VAR3 = '0.0193835837606681';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.00661682601704341'; $VAR2 = '0.00262751364088144'; $VAR3 = '0.0641858176542614'; $VAR4 = '0.0574769943513'; $VAR5 = '0.00149616285645223'; $VAR6 = '6.32016594720966e-17'; $VAR7 = '2.02026174620429e-08'; $VAR8 = '1.95048089267929e-32'; $VAR9 = '4.72125179873454e-246'; $VAR10 = '1.08331191332337e-36'; $VAR11 = '0.000948350775255532'; $VAR12 = '9.39148464336829e-18'; $VAR13 = '1.65616927530841e-05'; $VAR14 = '0.00195506943296058'; $VAR15 = '0.00551844634706239'; $VAR16 = '0.00573007455193584'; $VAR17 = '0.0729218826514669'; $VAR18 = '3.11573825943443e-05'; $VAR19 = '0.000611901263853316'; $VAR20 = '9.49153857315836e-08'; $VAR21 = '2.51407030744978e-07'; $VAR22 = '0.000410571186846331'; $VAR23 = '0.0394377371119832'; $VAR24 = '0.00398524191227274'; $VAR25 = '0.0204107994246112'; $VAR26 = '0.0655064637440605'; $VAR27 = '5.81512588804644e-06'; $VAR28 = '0.060677258282364'; $VAR29 = '0.0370528595507838';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.612949852031724'; $VAR2 = '0.180491087031057'; $VAR3 = '0.206559060937218';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.440960331618307'; $VAR3 = 17; $VAR4 = '0.559039668381694';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0575 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0575 Test, Z-Score-Based Method
0.00943396226415094
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.990654205607477

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0575 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0575 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '1.17365971664262e-11'; $VAR2 = '1.64209375528553e-19'; $VAR3 = '6.77162344238727e-11';

Control Chi-Square-Based P-Values
$VAR1 = '8.48655854350562e-20'; $VAR2 = '3.42177563345208e-40'; $VAR3 = '0.000177764749247546'; $VAR4 = '3.65018617393958e-05'; $VAR5 = '9.35549927295171e-32'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = 0; $VAR12 = 0; $VAR13 = 0; $VAR14 = '1.94844688649912e-31'; $VAR15 = '7.08629890517145e-12'; $VAR16 = '7.89975151305307e-12'; $VAR17 = '0.0798158638052699'; $VAR18 = 0; $VAR19 = '5.51778440804997e-52'; $VAR20 = '2.09909775259158e-26'; $VAR21 = 0; $VAR22 = '3.54419588397515e-13'; $VAR23 = '0.00513752112387051'; $VAR24 = '0.00306309424026972'; $VAR25 = '0.0561620452412064'; $VAR26 = '2.72841106314205e-05'; $VAR27 = '8.93492043062762e-20'; $VAR28 = '0.0207769598490118'; $VAR29 = '0.00204173136499947';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.147717795668878'; $VAR2 = '2.06675296402177e-09'; $VAR3 = '0.852282202264369';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 3; $VAR2 = '8.48405707061343e-10'; $VAR3 = 17; $VAR4 = '0.999999999151594';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>6.09446109814854e-11 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>6.09446109814854e-11 Test, Chi-Square-Based Method
0.423809523809524
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
0.702341137123746

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>6.09446109814854e-11 Test, Chi-Square-Based Method
1
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
0.5

Percentage of Samples in the Best Control Candidate that Meet the P-Value>6.09446109814854e-11 Test, Chi-Square-Based Method
0.4
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
0.714285714285714
Sample 5 - 'Paedagogus'
testsize: 3571
$VAR1 = 49; $VAR2 = 19; $VAR3 = 71; $VAR4 = 196; $VAR5 = 24; $VAR6 = 92; $VAR7 = 29; $VAR8 = 30; $VAR9 = 42; $VAR10 = 33; $VAR11 = 20; $VAR12 = 22; $VAR13 = 16; $VAR14 = 27; $VAR15 = 16; $VAR16 = 8; $VAR17 = 1; $VAR18 = 5; $VAR19 = 20; $VAR20 = 5; $VAR21 = 10; $VAR22 = 13;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0769346535070946'; $VAR2 = '2.87208030662372e-05'; $VAR3 = '0.02613448801892';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.0174763922156493'; $VAR2 = '0.00209530168984176'; $VAR3 = '0.0377352939171563'; $VAR4 = '0.0706070269935693'; $VAR5 = '0.0282967388074982'; $VAR6 = '4.35156742618701e-22'; $VAR7 = '4.66881389503218e-08'; $VAR8 = '0'; $VAR9 = '5.48944574512418e-225'; $VAR10 = '5.6323005811305e-297'; $VAR11 = '0.00697520586342957'; $VAR12 = '6.15511210496074e-18'; $VAR13 = '0.000490583457814558'; $VAR14 = '0.00583602538079451'; $VAR15 = '0.0138881204650957'; $VAR16 = '0.00841514689909191'; $VAR17 = '0.0709678959077672'; $VAR18 = '8.48417373195019e-09'; $VAR19 = '8.20036595852988e-05'; $VAR20 = '2.16583167548767e-09'; $VAR21 = '2.35708365869804e-08'; $VAR22 = '3.33233921350691e-05'; $VAR23 = '0.0108190367378341'; $VAR24 = '1.48405765565242e-05'; $VAR25 = '0.0553862507938739'; $VAR26 = '0.068069726403968'; $VAR27 = '5.17481875611916e-07'; $VAR28 = '0.0437603213815206'; $VAR29 = '0.00496120601844224';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.746229376332991'; $VAR2 = '0.00027857806570773'; $VAR3 = '0.253492045601301';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.520171246617902'; $VAR3 = 17; $VAR4 = '0.479828753382098';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0769 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0769 Test, Z-Score-Based Method
0.00526315789473684
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.994764397905759

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0769 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0769 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '2.39402724773204e-08'; $VAR2 = '4.95864675531872e-11'; $VAR3 = '6.03151747416443e-11';

Control Chi-Square-Based P-Values
$VAR1 = '2.32886659703646e-16'; $VAR2 = '3.66130660275547e-38'; $VAR3 = '9.39707053762154e-05'; $VAR4 = '0.00948870116428878'; $VAR5 = '2.54198251426615e-07'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '1.24918461921008e-33'; $VAR12 = 0; $VAR13 = '3.03726790643954e-45'; $VAR14 = '5.08169805126563e-25'; $VAR15 = '1.2519315301528e-06'; $VAR16 = '1.77256205501361e-09'; $VAR17 = '0.0199821593232741'; $VAR18 = 0; $VAR19 = 0; $VAR20 = '1.17985389206863e-27'; $VAR21 = 0; $VAR22 = '1.19457701937622e-17'; $VAR23 = '2.29884052195324e-09'; $VAR24 = 0; $VAR25 = '0.938459001216198'; $VAR26 = '1.14100845883765e-09'; $VAR27 = 0; $VAR28 = '0.000350286217818192'; $VAR29 = '7.53172606622279e-14';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.995430318227709'; $VAR2 = '0.00206179245549598'; $VAR3 = '0.00250788931679507';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '2.5510194729417e-08'; $VAR3 = 25; $VAR4 = '0.999999974489805';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>2.15462452295883e-08 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>2.15462452295883e-08 Test, Chi-Square-Based Method
0.00526315789473684
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
0.994764397905759

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>2.15462452295883e-08 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>2.15462452295883e-08 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 6 - 'Paedagogus'
testsize: 3593
$VAR1 = 36; $VAR2 = 27; $VAR3 = 57; $VAR4 = 172; $VAR5 = 25; $VAR6 = 93; $VAR7 = 38; $VAR8 = 8; $VAR9 = 47; $VAR10 = 41; $VAR11 = 16; $VAR12 = 16; $VAR13 = 11; $VAR14 = 15; $VAR15 = 9; $VAR16 = 3; $VAR17 = 13; $VAR18 = 3; $VAR19 = 16; $VAR20 = 9; $VAR21 = 9; $VAR22 = 22;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0791338063848208'; $VAR2 = '0.00045044407128294'; $VAR3 = '0.048907497492681';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.0196378102812021'; $VAR2 = '0.0167965441013452'; $VAR3 = '0.030357653980245'; $VAR4 = '0.0445505367265872'; $VAR5 = '0.0151455148448875'; $VAR6 = '2.98089409465241e-19'; $VAR7 = '1.30746700302077e-09'; $VAR8 = '0'; $VAR9 = '4.55831852824733e-210'; $VAR10 = '1.48200969739963e-138'; $VAR11 = '0.0142010136540696'; $VAR12 = '3.82729325067173e-18'; $VAR13 = '0.000861146647806824'; $VAR14 = '0.00964437499762617'; $VAR15 = '0.019197872462059'; $VAR16 = '0.034159009054761'; $VAR17 = '0.0919491959012697'; $VAR18 = '1.22419426991556e-18'; $VAR19 = '0.00044690639174449'; $VAR20 = '2.52702633847549e-10'; $VAR21 = '1.17597692723097e-06'; $VAR22 = '1.6894306234232e-05'; $VAR23 = '0.0282633459451501'; $VAR24 = '8.41803276947549e-07'; $VAR25 = '0.0164067951620403'; $VAR26 = '0.0187867878302213'; $VAR27 = '8.44913618131535e-07'; $VAR28 = '0.0386907775664471'; $VAR29 = '0.00687746649393025';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.615866836961099'; $VAR2 = '0.00350562645830362'; $VAR3 = '0.380627536580598';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.462546280620507'; $VAR3 = 17; $VAR4 = '0.537453719379493';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0791 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0791 Test, Z-Score-Based Method
0.00526315789473684
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.994764397905759

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0791 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0791 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '1.0237570007237e-05'; $VAR2 = '6.06687490003521e-06'; $VAR3 = '6.96041042081951e-06';

Control Chi-Square-Based P-Values
$VAR1 = '3.49609752145441e-14'; $VAR2 = '7.95654032140336e-15'; $VAR3 = '9.17658781031183e-05'; $VAR4 = '0.0263155719186672'; $VAR5 = '0.00709681132856707'; $VAR6 = '1.78252010080424e-40'; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '2.19526675637316e-29'; $VAR12 = 0; $VAR13 = '3.93042422817008e-43'; $VAR14 = '8.27772778257574e-10'; $VAR15 = '8.11849406214223e-05'; $VAR16 = '0.0370929996870314'; $VAR17 = '0.967301715548532'; $VAR18 = 0; $VAR19 = 0; $VAR20 = '1.23469291389753e-16'; $VAR21 = 0; $VAR22 = '1.95432235881395e-09'; $VAR23 = '0.0501513473459013'; $VAR24 = '2.26733246945969e-47'; $VAR25 = '0.122771537975221'; $VAR26 = '3.83993321420507e-11'; $VAR27 = '1.18556918584391e-18'; $VAR28 = '0.00395597736744429'; $VAR29 = '2.49806932381708e-09';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.440044430230151'; $VAR2 = '0.260774237126229'; $VAR3 = '0.29918133264362';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '1.05835247607888e-05'; $VAR3 = 17; $VAR4 = '0.999989416475239';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>1e-05 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>1e-05 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>1e-05 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>1e-05 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Peter Kirby
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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Peter Kirby » Mon Jun 01, 2015 3:00 pm

Sample 7 - 'Paedagogus'
testsize: 3548
$VAR1 = 62; $VAR2 = 20; $VAR3 = 84; $VAR4 = 203; $VAR5 = 17; $VAR6 = 114; $VAR7 = 25; $VAR8 = 18; $VAR9 = 65; $VAR10 = 27; $VAR11 = 30; $VAR12 = 6; $VAR13 = 13; $VAR14 = 12; $VAR15 = 8; $VAR16 = 0; $VAR17 = 6; $VAR18 = 3; $VAR19 = 10; $VAR20 = 8; $VAR21 = 12; $VAR22 = 24;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.134698681085821'; $VAR2 = '0.000211711288683172'; $VAR3 = '0.0430126073189553';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0239833016227674'; $VAR2 = '0.00555156211982654'; $VAR3 = '0.0677401748300897'; $VAR4 = '0.0814445517831272'; $VAR5 = '0.0228743151044276'; $VAR6 = '1.46615053994089e-14'; $VAR7 = '7.14969674733078e-09'; $VAR8 = '6.90407058847465e-314'; $VAR9 = '3.8206818941778e-192'; $VAR10 = '1.07237809052077e-260'; $VAR11 = '0.0120885384092325'; $VAR12 = '6.04266468592976e-15'; $VAR13 = '0.000361754567519932'; $VAR14 = '0.0132247136824641'; $VAR15 = '0.0154925852252336'; $VAR16 = '0.0183447714784034'; $VAR17 = '0.0750033158704843'; $VAR18 = '2.24802463397297e-07'; $VAR19 = '0.000318540202301619'; $VAR20 = '1.50586545606054e-06'; $VAR21 = '4.48302459536444e-05'; $VAR22 = '0.00118726508926995'; $VAR23 = '0.0439388806757861'; $VAR24 = '4.99244367256404e-05'; $VAR25 = '0.0255496538380448'; $VAR26 = '0.0144246633743612'; $VAR27 = '0.000424132966373107'; $VAR28 = '0.0337279869082186'; $VAR29 = '0.0129457193012898';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.757061657671527'; $VAR2 = '0.00118990399806616'; $VAR3 = '0.241748438330407';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.623191757141393'; $VAR3 = 4; $VAR4 = '0.376808242858607';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '6.49499220165349e-05'; $VAR2 = '9.22332240328988e-12'; $VAR3 = '4.23324792557397e-16';

Control Chi-Square-Based P-Values
$VAR1 = '1.67626122341358e-25'; $VAR2 = '1.65737631781377e-19'; $VAR3 = '0.00963124420366487'; $VAR4 = '0.0558111011425601'; $VAR5 = '2.58258631498435e-06'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '1.31342583709399e-23'; $VAR12 = 0; $VAR13 = 0; $VAR14 = '1.47778853269824e-18'; $VAR15 = '0.000370744667287126'; $VAR16 = '5.32775094285026e-06'; $VAR17 = '0.762535557710638'; $VAR18 = 0; $VAR19 = 0; $VAR20 = '6.35627710326099e-26'; $VAR21 = 0; $VAR22 = 0; $VAR23 = '3.19127581552657e-05'; $VAR24 = '1.47208953863741e-16'; $VAR25 = '0.649595839371413'; $VAR26 = '8.3758614950104e-15'; $VAR27 = 0; $VAR28 = '0.00033007809766167'; $VAR29 = '1.84710014478697e-09';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.999999857986828'; $VAR2 = '1.42006653851078e-07'; $VAR3 = '6.51770963376878e-12';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '8.51689991895748e-05'; $VAR3 = 17; $VAR4 = '0.99991483100081';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>6.4e-05 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>6.4e-05 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>6.4e-05 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>6.4e-05 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 8 - 'Paedagogus'
testsize: 3443
$VAR1 = 60; $VAR2 = 16; $VAR3 = 54; $VAR4 = 180; $VAR5 = 15; $VAR6 = 114; $VAR7 = 27; $VAR8 = 26; $VAR9 = 57; $VAR10 = 38; $VAR11 = 11; $VAR12 = 23; $VAR13 = 9; $VAR14 = 14; $VAR15 = 11; $VAR16 = 0; $VAR17 = 5; $VAR18 = 14; $VAR19 = 9; $VAR20 = 9; $VAR21 = 9; $VAR22 = 13;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0886934976927316'; $VAR2 = '0.00170997984299546'; $VAR3 = '0.0262380355315333';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.00337408467375469'; $VAR2 = '0.00176534799752388'; $VAR3 = '0.0406554868548226'; $VAR4 = '0.0622925015710056'; $VAR5 = '0.0209342453715624'; $VAR6 = '1.79682046104132e-10'; $VAR7 = '2.2080776042888e-08'; $VAR8 = '0'; $VAR9 = '4.95007048402865e-198'; $VAR10 = '4.3948181041226e-100'; $VAR11 = '0.000306623305599251'; $VAR12 = '2.67933236691197e-16'; $VAR13 = '0.000386095731639967'; $VAR14 = '0.0156234866082849'; $VAR15 = '0.0231835310434587'; $VAR16 = '0.0203244298316576'; $VAR17 = '0.0492383452704838'; $VAR18 = '0.000815216502474463'; $VAR19 = '9.24461685990565e-05'; $VAR20 = '2.2555257277703e-10'; $VAR21 = '5.34720838356336e-07'; $VAR22 = '2.42521396498065e-05'; $VAR23 = '0.0205458213188055'; $VAR24 = '3.59267392315659e-08'; $VAR25 = '0.0105253282392865'; $VAR26 = '0.0232823588518723'; $VAR27 = '5.59545338772634e-06'; $VAR28 = '0.0211146025969272'; $VAR29 = '0.00915434629937404';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.760393922887362'; $VAR2 = '0.0146601308404617'; $VAR3 = '0.224945946272176';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.587428623350731'; $VAR3 = 4; $VAR4 = '0.412571376649269';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0886 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0886 Test, Z-Score-Based Method
0.00510204081632653
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.99492385786802

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0886 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0886 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '2.07824476831905e-08'; $VAR2 = '9.00663999279797e-12'; $VAR3 = '5.92707925746515e-14';

Control Chi-Square-Based P-Values
$VAR1 = '2.56144418314458e-24'; $VAR2 = '3.38339782007974e-45'; $VAR3 = '0.00104681839204147'; $VAR4 = '0.0659251397433351'; $VAR5 = '0.00555066555805928'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '1.69316113070872e-53'; $VAR12 = 0; $VAR13 = 0; $VAR14 = '5.61727550698164e-13'; $VAR15 = '0.000586974652480733'; $VAR16 = '1.24706580370919e-05'; $VAR17 = '0.400168786543349'; $VAR18 = 0; $VAR19 = 0; $VAR20 = '2.24818078066087e-24'; $VAR21 = 0; $VAR22 = '1.51744822720691e-10'; $VAR23 = '2.8469583881268e-05'; $VAR24 = 0; $VAR25 = '0.026070570645435'; $VAR26 = '4.79269530107177e-17'; $VAR27 = '3.14799950777994e-17'; $VAR28 = '1.9206343394787e-06'; $VAR29 = '2.47987795029184e-14';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.999563961000511'; $VAR2 = '0.000433188279058603'; $VAR3 = '2.85072043008088e-06';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '5.19342020235738e-08'; $VAR3 = 17; $VAR4 = '0.999999948065798';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>1.87042029148715e-08 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>1.87042029148715e-08 Test, Chi-Square-Based Method
0.0102040816326531
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
0.98989898989899

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>1.87042029148715e-08 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>1.87042029148715e-08 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 9 - 'Paedagogus'
testsize: 3422
$VAR1 = 50; $VAR2 = 20; $VAR3 = 58; $VAR4 = 171; $VAR5 = 21; $VAR6 = 105; $VAR7 = 18; $VAR8 = 13; $VAR9 = 52; $VAR10 = 36; $VAR11 = 19; $VAR12 = 15; $VAR13 = 12; $VAR14 = 18; $VAR15 = 10; $VAR16 = 0; $VAR17 = 5; $VAR18 = 1; $VAR19 = 18; $VAR20 = 7; $VAR21 = 10; $VAR22 = 15;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0983761277319433'; $VAR2 = '0.000848038817131552'; $VAR3 = '0.0421993491935228';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.023110465490545'; $VAR2 = '0.00868769425371688'; $VAR3 = '0.0394322177350656'; $VAR4 = '0.0658086266489784'; $VAR5 = '0.0124044103379228'; $VAR6 = '5.26176083499762e-11'; $VAR7 = '6.68781333369414e-08'; $VAR8 = '2.86656887717091e-319'; $VAR9 = '2.54053580344501e-167'; $VAR10 = '2.04752742806399e-77'; $VAR11 = '0.0199804553782795'; $VAR12 = '2.5454187456886e-14'; $VAR13 = '0.00223651374118813'; $VAR14 = '0.0285473845182935'; $VAR15 = '0.042144367481065'; $VAR16 = '0.0148783567483874'; $VAR17 = '0.0681423318218486'; $VAR18 = '0.00113918849695221'; $VAR19 = '0.000108172915792181'; $VAR20 = '8.67243039384675e-09'; $VAR21 = '2.04626346289693e-06'; $VAR22 = '5.5728783321053e-05'; $VAR23 = '0.0303206718491381'; $VAR24 = '6.83562696665999e-07'; $VAR25 = '0.0172773245871027'; $VAR26 = '0.0280163297753358'; $VAR27 = '2.66975393567823e-05'; $VAR28 = '0.020251735102102'; $VAR29 = '0.00543957654806096';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.695613648235106'; $VAR2 = '0.00599644841721409'; $VAR3 = '0.29838990334768';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.590782115061327'; $VAR3 = 17; $VAR4 = '0.409217884938672';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0983 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0983 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0983 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0983 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.000115015292193819'; $VAR2 = '4.07927684540326e-07'; $VAR3 = '1.13728404392721e-08';

Control Chi-Square-Based P-Values
$VAR1 = '0.000248397122920209'; $VAR2 = '3.16779254020801e-15'; $VAR3 = '0.00351602729964401'; $VAR4 = '0.370584456444289'; $VAR5 = '0.151033698238421'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '4.19228785635805e-05'; $VAR12 = 0; $VAR13 = '1.01086087829593e-31'; $VAR14 = '0.000103255376552654'; $VAR15 = '0.473724046104095'; $VAR16 = '0.0130890786319929'; $VAR17 = '0.95228021908735'; $VAR18 = '1.56181921429088e-25'; $VAR19 = 0; $VAR20 = '1.94887227408445e-15'; $VAR21 = 0; $VAR22 = '4.63830572730639e-09'; $VAR23 = '0.00500941291147478'; $VAR24 = 0; $VAR25 = '0.851932649450978'; $VAR26 = '5.94032623962248e-08'; $VAR27 = '5.58696230287909e-13'; $VAR28 = '0.00252565148183242'; $VAR29 = '2.03108605592853e-10';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.99636763542796'; $VAR2 = '0.00353384262838826'; $VAR3 = '9.85219436514719e-05';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.000120764245810982'; $VAR3 = 17; $VAR4 = '0.999879235754189';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0001 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0001 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0001 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0001 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 10 - 'Paedagogus'
testsize: 3331
$VAR1 = 37; $VAR2 = 26; $VAR3 = 60; $VAR4 = 190; $VAR5 = 11; $VAR6 = 113; $VAR7 = 18; $VAR8 = 17; $VAR9 = 45; $VAR10 = 24; $VAR11 = 14; $VAR12 = 7; $VAR13 = 8; $VAR14 = 12; $VAR15 = 12; $VAR16 = 1; $VAR17 = 6; $VAR18 = 3; $VAR19 = 13; $VAR20 = 5; $VAR21 = 17; $VAR22 = 15;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.197925973596406'; $VAR2 = '0.00751532307398305'; $VAR3 = '0.0672294446801052';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0225426713127801'; $VAR2 = '0.00729954899797692'; $VAR3 = '0.0572517614075777'; $VAR4 = '0.0675367053738234'; $VAR5 = '0.0129220303817959'; $VAR6 = '6.5200154636536e-09'; $VAR7 = '1.8504512402572e-07'; $VAR8 = '2.36653177223933e-08'; $VAR9 = '6.35504646561675e-234'; $VAR10 = '1.05696094134945e-83'; $VAR11 = '0.0289923081147831'; $VAR12 = '3.49652071863808e-15'; $VAR13 = '0.00196691918893149'; $VAR14 = '0.00969093011801135'; $VAR15 = '0.0254242328953202'; $VAR16 = '0.0154826544454785'; $VAR17 = '0.0620735714163949'; $VAR18 = '2.99167258624238e-06'; $VAR19 = '6.13004148439611e-05'; $VAR20 = '2.7057862862916e-07'; $VAR21 = '8.78674336510903e-06'; $VAR22 = '0.00080449215512034'; $VAR23 = '0.0215648390486527'; $VAR24 = '8.71268056316788e-05'; $VAR25 = '0.00883382779023209'; $VAR26 = '0.0527926763666622'; $VAR27 = '0.0015326689252114'; $VAR28 = '0.037538047914724'; $VAR29 = '0.0241731894456987';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.725879031303874'; $VAR2 = '0.0275618976820206'; $VAR3 = '0.246559071014105';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.745588699564818'; $VAR3 = 4; $VAR4 = '0.254411300435182';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.337773298546972'; $VAR2 = '8.00293995298483e-06'; $VAR3 = '5.92845365809375e-05';

Control Chi-Square-Based P-Values
$VAR1 = '8.65231259672672e-06'; $VAR2 = '3.53159682166032e-11'; $VAR3 = '0.109027650888284'; $VAR4 = '0.828600953740382'; $VAR5 = '0.109183972024777'; $VAR6 = 0; $VAR7 = 0; $VAR8 = '7.1778920513372e-54'; $VAR9 = 0; $VAR10 = 0; $VAR11 = '1.19793529999286e-05'; $VAR12 = 0; $VAR13 = '3.08998302869524e-20'; $VAR14 = '0.00197991290166231'; $VAR15 = '0.172297672504217'; $VAR16 = '0.0305885344143684'; $VAR17 = '0.997913277066163'; $VAR18 = 0; $VAR19 = 0; $VAR20 = '7.11606721637371e-15'; $VAR21 = 0; $VAR22 = 0; $VAR23 = '0.000758693949540514'; $VAR24 = '4.49741023771765e-46'; $VAR25 = '0.0225622505208646'; $VAR26 = '5.20872422796768e-05'; $VAR27 = 0; $VAR28 = '0.0767438481226161'; $VAR29 = '0.000303726063980842';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.999800830689628'; $VAR2 = '2.36885095635845e-05'; $VAR3 = '0.000175480800808262';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.252883651534732'; $VAR3 = 17; $VAR4 = '0.747116348465268';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.3 Test, Chi-Square-Based Method
0.666666666666667
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.3 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.3 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.3 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 11 - 'Paedagogus'
testsize: 3293
$VAR1 = 49; $VAR2 = 27; $VAR3 = 54; $VAR4 = 178; $VAR5 = 13; $VAR6 = 75; $VAR7 = 16; $VAR8 = 33; $VAR9 = 32; $VAR10 = 27; $VAR11 = 14; $VAR12 = 10; $VAR13 = 7; $VAR14 = 13; $VAR15 = 10; $VAR16 = 2; $VAR17 = 2; $VAR18 = 2; $VAR19 = 6; $VAR20 = 3; $VAR21 = 18; $VAR22 = 10;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.15084833489752'; $VAR2 = '0.00748977154034033'; $VAR3 = '0.0611410668655216';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0267586986717974'; $VAR2 = '0.00151388895050831'; $VAR3 = '0.0708446108986705'; $VAR4 = '0.0755224295657931'; $VAR5 = '0.00121267522506594'; $VAR6 = '1.20815009403709e-08'; $VAR7 = '9.88458787565168e-06'; $VAR8 = '7.58980819933296e-10'; $VAR9 = '2.03387030410051e-206'; $VAR10 = '1.51204381419415e-101'; $VAR11 = '1.22032605605344e-05'; $VAR12 = '8.19124822607543e-15'; $VAR13 = '0.00159439598272123'; $VAR14 = '0.00623011708352471'; $VAR15 = '0.00363444794183841'; $VAR16 = '0.00946505174948597'; $VAR17 = '0.0285384735886039'; $VAR18 = '6.56579892718768e-08'; $VAR19 = '0.000509741158379729'; $VAR20 = '1.97928169345189e-06'; $VAR21 = '1.76995609953449e-06'; $VAR22 = '9.02965820167623e-05'; $VAR23 = '0.0141506955861276'; $VAR24 = '0.00673807065503651'; $VAR25 = '0.0219565860213917'; $VAR26 = '0.0774010837997949'; $VAR27 = '9.94910510742039e-05'; $VAR28 = '0.0420292038180515'; $VAR29 = '0.047292591209403';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.687301362708366'; $VAR2 = '0.0341252038979906'; $VAR3 = '0.278573433393643';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.660892526072815'; $VAR3 = 26; $VAR4 = '0.339107473927185';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.293376991863536'; $VAR2 = '3.21663243250075e-06'; $VAR3 = '0.17101335747527';

Control Chi-Square-Based P-Values
$VAR1 = '0.0459891402513635'; $VAR2 = 0; $VAR3 = '0.767138490820904'; $VAR4 = '0.972444531088379'; $VAR5 = '1.08955333224706e-38'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = '1.7704502984314e-14'; $VAR12 = 0; $VAR13 = '3.42696325802468e-23'; $VAR14 = '5.61039414077867e-07'; $VAR15 = '0.0020963773721122'; $VAR16 = '0.00254045716264803'; $VAR17 = '0.876106336176146'; $VAR18 = 0; $VAR19 = '5.19638721172577e-33'; $VAR20 = '1.01271723496656e-11'; $VAR21 = 0; $VAR22 = '5.00829330701302e-10'; $VAR23 = '0.0706023252710813'; $VAR24 = '0.943006322950669'; $VAR25 = '0.999986875113872'; $VAR26 = '0.382583352804129'; $VAR27 = '1.19998871123148e-13'; $VAR28 = '0.937223417873039'; $VAR29 = '0.971438572105067';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.631742154415864'; $VAR2 = '6.9265223900625e-06'; $VAR3 = '0.368250919061746';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.226832525133981'; $VAR3 = 25; $VAR4 = '0.773167474866019';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Chi-Square-Based Method
0.833333333333333
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
Sample 12 - 'Paedagogus'
testsize: 3255
$VAR1 = 50; $VAR2 = 17; $VAR3 = 62; $VAR4 = 178; $VAR5 = 13; $VAR6 = 111; $VAR7 = 40; $VAR8 = 21; $VAR9 = 37; $VAR10 = 34; $VAR11 = 25; $VAR12 = 1; $VAR13 = 9; $VAR14 = 14; $VAR15 = 6; $VAR16 = 4; $VAR17 = 1; $VAR18 = 1; $VAR19 = 9; $VAR20 = 11; $VAR21 = 4; $VAR22 = 16;

22 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'TE' ]; $VAR6 = [ 'DE', 'D' ]; $VAR7 = [ 'MEN' ]; $VAR8 = [ 'ALLA', 'ALL' ]; $VAR9 = [ 'GAR' ]; $VAR10 = [ 'EIS' ]; $VAR11 = [ 'EN' ]; $VAR12 = [ 'EK', 'EC' ]; $VAR13 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR14 = [ 'PROS' ]; $VAR15 = [ 'OUN' ]; $VAR16 = [ 'INA' ]; $VAR17 = [ 'OTI' ]; $VAR18 = [ 'APO', 'AP' ]; $VAR19 = [ 'PERI' ]; $VAR20 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR21 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR22 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.12066380657107'; $VAR2 = '0.00412899464131604'; $VAR3 = '0.0187684367405723';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0389219708806368'; $VAR2 = '0.000339770810365796'; $VAR3 = '0.0342252826583724'; $VAR4 = '0.0180555461594469'; $VAR5 = '0.00579240615007259'; $VAR6 = '5.52022318387063e-11'; $VAR7 = '3.13328349714052e-10'; $VAR8 = '2.70242094905335e-15'; $VAR9 = '1.01888260436109e-257'; $VAR10 = '1.98037340365993e-50'; $VAR11 = '3.23094830116569e-05'; $VAR12 = '1.44567199567569e-23'; $VAR13 = '0.0010814774318072'; $VAR14 = '0.00914502131078242'; $VAR15 = '0.0270039406018487'; $VAR16 = '0.0310441024542801'; $VAR17 = '0.0536782930440017'; $VAR18 = '2.10479105044059e-05'; $VAR19 = '0.00202216922685127'; $VAR20 = '2.92809340444809e-08'; $VAR21 = '1.24766636340592e-05'; $VAR22 = '6.99407860857346e-05'; $VAR23 = '0.0393055607566336'; $VAR24 = '0.000412504206878313'; $VAR25 = '0.0137109612909148'; $VAR26 = '0.035887264953318'; $VAR27 = '5.31155852807184e-07'; $VAR28 = '0.0250960713727831'; $VAR29 = '0.0188360279329279';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.840504082380571'; $VAR2 = '0.0287612081101516'; $VAR3 = '0.130734709509277';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.692109403508863'; $VAR3 = 17; $VAR4 = '0.307890596491137';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1

Author Chi-Square-Based P-Values
$VAR1 = '0.0150642933556406'; $VAR2 = '6.57959567335829e-15'; $VAR3 = '6.31928250687397e-05';

Control Chi-Square-Based P-Values
$VAR1 = '0.0019258938441265'; $VAR2 = 0; $VAR3 = '1.03755731220104e-05'; $VAR4 = '2.26587602767057e-08'; $VAR5 = '0.000146136466734442'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = 0; $VAR12 = 0; $VAR13 = '4.9267941589024e-35'; $VAR14 = '1.88186593738808e-05'; $VAR15 = '0.178211877844096'; $VAR16 = '0.0802419461351041'; $VAR17 = '0.72438504419326'; $VAR18 = 0; $VAR19 = '1.4641389234413e-40'; $VAR20 = '1.08245643087088e-12'; $VAR21 = '7.10186412739422e-42'; $VAR22 = '4.10168596272583e-09'; $VAR23 = '0.0784670296402985'; $VAR24 = '1.11588527249125e-14'; $VAR25 = '0.00870983536155261'; $VAR26 = '7.80618533264245e-09'; $VAR27 = '5.71301724235525e-18'; $VAR28 = '0.000342425833047638'; $VAR29 = '0.000452153210780152';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '0.995822648633064'; $VAR2 = '4.3494309594847e-13'; $VAR3 = '0.00417735136650106';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.020372313004668'; $VAR3 = 17; $VAR4 = '0.979627686995332';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.015 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.015 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.015 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.015 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

Stephan Huller
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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Stephan Huller » Mon Jun 01, 2015 3:52 pm

Why not test the Letter to Theodore?

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Peter Kirby
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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Peter Kirby » Mon Jun 01, 2015 3:55 pm

Stephan Huller wrote:Why not test the Letter to Theodore?
I'm working up to the interesting stuff.

(As a serious question, though, it might be too short to get a significant result, with this method. Not that I won't try...)
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Peter Kirby
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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Peter Kirby » Mon Jun 01, 2015 4:51 pm

Further analysis, performed with the 'Stromata' (also with the quotations removed), suggests that the frequency of 'te' and the frequency of 'kata' may not be invariant across Clement's works. Of the three author candidates, 'Clement' (the author of the Protrepticus and Paedagogus) was selected 13 out of 16 times (for 81.25% accuracy). Of the 32 candidates, 'Clement' was selected 9 out of 16 times (for 56.25% accuracy). This is when including these two words.

When removing these two words from the list, the situation improved. With twenty words now, 16 out of 16 samples (for 100% accuracy) from the 'Stromata' are identified with the author designated as 'Clement' (the author of the Protrepticus and Paedagogus), while 13 out of 16 samples are correctly identified with this same 'Clement' as the best author when pitted against 31 other candidates, including the controls (for 81.25% accuracy).
testsize: 3953
$VAR1 = 48; $VAR2 = 39; $VAR3 = 82; $VAR4 = 202; $VAR5 = 133; $VAR6 = 47; $VAR7 = 21; $VAR8 = 40; $VAR9 = 31; $VAR10 = 24; $VAR11 = 10; $VAR12 = 28; $VAR13 = 15; $VAR14 = 2; $VAR15 = 12; $VAR16 = 8; $VAR17 = 8; $VAR18 = 17; $VAR19 = 13; $VAR20 = 14;

20 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'DE', 'D' ]; $VAR6 = [ 'MEN' ]; $VAR7 = [ 'ALLA', 'ALL' ]; $VAR8 = [ 'GAR' ]; $VAR9 = [ 'EIS' ]; $VAR10 = [ 'EN' ]; $VAR11 = [ 'EK', 'EC' ]; $VAR12 = [ 'PROS' ]; $VAR13 = [ 'OUN' ]; $VAR14 = [ 'INA' ]; $VAR15 = [ 'OTI' ]; $VAR16 = [ 'APO', 'AP' ]; $VAR17 = [ 'PERI' ]; $VAR18 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR19 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR20 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.195530031280083'; $VAR2 = '6.84169903116509e-07'; $VAR3 = '0.0367431015083052';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.841808318477815'; $VAR2 = '2.94553175246335e-06'; $VAR3 = '0.158188735990432';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.491529796355276'; $VAR3 = 17; $VAR4 = '0.508470203644724';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0481927710843374
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.954022988505747

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 3977
$VAR1 = 40; $VAR2 = 20; $VAR3 = 85; $VAR4 = 227; $VAR5 = 138; $VAR6 = 40; $VAR7 = 33; $VAR8 = 43; $VAR9 = 21; $VAR10 = 40; $VAR11 = 13; $VAR12 = 28; $VAR13 = 18; $VAR14 = 3; $VAR15 = 5; $VAR16 = 11; $VAR17 = 21; $VAR18 = 7; $VAR19 = 21; $VAR20 = 9;

Author Z-Score-Based P-Values
$VAR1 = '0.17677388204396'; $VAR2 = '3.89858854616302e-06'; $VAR3 = '0.0463918597764056';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.792105421329078'; $VAR2 = '1.7469170712556e-05'; $VAR3 = '0.207877109500209';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.587873051777315'; $VAR3 = 17; $VAR4 = '0.412126948222685';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0426829268292683
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.95906432748538

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 3846
$VAR1 = 47; $VAR2 = 25; $VAR3 = 64; $VAR4 = 208; $VAR5 = 141; $VAR6 = 30; $VAR7 = 31; $VAR8 = 32; $VAR9 = 30; $VAR10 = 30; $VAR11 = 15; $VAR12 = 21; $VAR13 = 12; $VAR14 = 6; $VAR15 = 4; $VAR16 = 7; $VAR17 = 16; $VAR18 = 7; $VAR19 = 12; $VAR20 = 15;

Author Z-Score-Based P-Values
$VAR1 = '0.271688056509543'; $VAR2 = '0.000338037790801476'; $VAR3 = '0.0722344973603708';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.789193021480961'; $VAR2 = '0.000981924155683285'; $VAR3 = '0.209825054363356';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.782416651840802'; $VAR3 = 17; $VAR4 = '0.217583348159198';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.647058823529412
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 3897
$VAR1 = 53; $VAR2 = 30; $VAR3 = 84; $VAR4 = 189; $VAR5 = 109; $VAR6 = 28; $VAR7 = 26; $VAR8 = 51; $VAR9 = 20; $VAR10 = 46; $VAR11 = 28; $VAR12 = 27; $VAR13 = 11; $VAR14 = 1; $VAR15 = 1; $VAR16 = 11; $VAR17 = 13; $VAR18 = 7; $VAR19 = 12; $VAR20 = 23;

Author Z-Score-Based P-Values
$VAR1 = '0.180887982397212'; $VAR2 = '0.000239971707624128'; $VAR3 = '0.103954066528819';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.634512067773162'; $VAR2 = '0.000841763739048642'; $VAR3 = '0.36464616848779';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.642808688372893'; $VAR3 = 17; $VAR4 = '0.357191311627107';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0476190476190476
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.954545454545454

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 4007
$VAR1 = 56; $VAR2 = 39; $VAR3 = 86; $VAR4 = 236; $VAR5 = 119; $VAR6 = 34; $VAR7 = 31; $VAR8 = 50; $VAR9 = 28; $VAR10 = 26; $VAR11 = 17; $VAR12 = 29; $VAR13 = 25; $VAR14 = 5; $VAR15 = 11; $VAR16 = 9; $VAR17 = 21; $VAR18 = 7; $VAR19 = 24; $VAR20 = 15;

Author Z-Score-Based P-Values
$VAR1 = '0.192470357857521'; $VAR2 = '2.41726647543524e-06'; $VAR3 = '0.0369147833168241';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.839061887949674'; $VAR2 = '1.053791448789e-05'; $VAR3 = '0.160927574135838';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.655860133103025'; $VAR3 = 26; $VAR4 = '0.344139866896975';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0368098159509202
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.964497041420118

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.25
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.8
testsize: 4018
$VAR1 = 47; $VAR2 = 37; $VAR3 = 78; $VAR4 = 212; $VAR5 = 102; $VAR6 = 27; $VAR7 = 37; $VAR8 = 53; $VAR9 = 31; $VAR10 = 39; $VAR11 = 24; $VAR12 = 33; $VAR13 = 21; $VAR14 = 9; $VAR15 = 16; $VAR16 = 5; $VAR17 = 21; $VAR18 = 3; $VAR19 = 9; $VAR20 = 12;

Author Z-Score-Based P-Values
$VAR1 = '0.113962170157634'; $VAR2 = '2.05594432674095e-10'; $VAR3 = '0.0133700715119295';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.894998536736418'; $VAR2 = '1.61462980346853e-09'; $VAR3 = '0.105001461648952';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.464812214287387'; $VAR3 = 26; $VAR4 = '0.535187785712613';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0245398773006135
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.976047904191617

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.125
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.888888888888889
testsize: 4083
$VAR1 = 39; $VAR2 = 35; $VAR3 = 93; $VAR4 = 206; $VAR5 = 111; $VAR6 = 29; $VAR7 = 27; $VAR8 = 41; $VAR9 = 24; $VAR10 = 31; $VAR11 = 20; $VAR12 = 31; $VAR13 = 20; $VAR14 = 6; $VAR15 = 14; $VAR16 = 6; $VAR17 = 7; $VAR18 = 2; $VAR19 = 20; $VAR20 = 19;

Author Z-Score-Based P-Values
$VAR1 = '0.184507104443449'; $VAR2 = '6.44767581679886e-07'; $VAR3 = '0.0296854891212661';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.861404897185442'; $VAR2 = '3.01021445261311e-06'; $VAR3 = '0.138592092600105';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.631811032844873'; $VAR3 = 26; $VAR4 = '0.368188967155127';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0368098159509202
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.964497041420118

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.125
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.888888888888889
testsize: 3859
$VAR1 = 54; $VAR2 = 31; $VAR3 = 82; $VAR4 = 171; $VAR5 = 101; $VAR6 = 33; $VAR7 = 33; $VAR8 = 45; $VAR9 = 26; $VAR10 = 39; $VAR11 = 16; $VAR12 = 29; $VAR13 = 17; $VAR14 = 2; $VAR15 = 3; $VAR16 = 3; $VAR17 = 13; $VAR18 = 5; $VAR19 = 21; $VAR20 = 25;

Author Z-Score-Based P-Values
$VAR1 = '0.202195346093348'; $VAR2 = '0.00015499050600685'; $VAR3 = '0.0632708989895781';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.761216796710709'; $VAR2 = '0.000583501939004259'; $VAR3 = '0.238199701350287';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.619351302640202'; $VAR3 = 26; $VAR4 = '0.380648697359798';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.647058823529412
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 4006
$VAR1 = 55; $VAR2 = 30; $VAR3 = 113; $VAR4 = 207; $VAR5 = 106; $VAR6 = 34; $VAR7 = 30; $VAR8 = 53; $VAR9 = 28; $VAR10 = 49; $VAR11 = 16; $VAR12 = 20; $VAR13 = 21; $VAR14 = 10; $VAR15 = 8; $VAR16 = 6; $VAR17 = 12; $VAR18 = 1; $VAR19 = 19; $VAR20 = 25;

Author Z-Score-Based P-Values
$VAR1 = '0.184348324313037'; $VAR2 = '8.57390591675386e-06'; $VAR3 = '0.0133212797243607';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.932567905223712'; $VAR2 = '4.33730521292668e-05'; $VAR3 = '0.0673887217241584';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.651876232266051'; $VAR3 = 26; $VAR4 = '0.348123767733949';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0368098159509202
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.964497041420118

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.25
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.8

Author Chi-Square-Based P-Values
$VAR1 = '0.0163100061367702'; $VAR2 = '5.5160305016132e-54'; $VAR3 = '3.46032764412908e-33';

Control Chi-Square-Based P-Values
$VAR1 = 0; $VAR2 = 0; $VAR3 = '0.00217216810036267'; $VAR4 = '3.5032461523e-05'; $VAR5 = '8.8635864475024e-24'; $VAR6 = 0; $VAR7 = 0; $VAR8 = 0; $VAR9 = 0; $VAR10 = 0; $VAR11 = 0; $VAR12 = 0; $VAR13 = 0; $VAR14 = '9.9450662554077e-49'; $VAR15 = '9.2397621227663e-27'; $VAR16 = '8.17723118023993e-22'; $VAR17 = '4.97668561014361e-07'; $VAR18 = 0; $VAR19 = 0; $VAR20 = '6.39970041962523e-60'; $VAR21 = '2.93085834895571e-47'; $VAR22 = '2.05804285834199e-38'; $VAR23 = '1.70880753379026e-15'; $VAR24 = '5.6404162669492e-22'; $VAR25 = '0.0387499083700053'; $VAR26 = '0.016914249311879'; $VAR27 = 0; $VAR28 = '0.00941726278015306'; $VAR29 = '1.22170597773957e-05';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Chi-Square-Based Method
$VAR1 = '1'; $VAR2 = '3.38199167759817e-52'; $VAR3 = '2.12159800254637e-31';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Chi-Square-Based Method
$VAR1 = 1; $VAR2 = '0.29622287435196'; $VAR3 = 25; $VAR4 = '0.70377712564804';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0163 Test, Chi-Square-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0163 Test, Chi-Square-Based Method
0.00613496932515337
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Chi-Square-Based Method
0.99390243902439

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0163 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Chi-Square-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0163 Test, Chi-Square-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Chi-Square-Based Method
1
testsize: 4204
$VAR1 = 42; $VAR2 = 34; $VAR3 = 78; $VAR4 = 232; $VAR5 = 118; $VAR6 = 41; $VAR7 = 26; $VAR8 = 54; $VAR9 = 24; $VAR10 = 39; $VAR11 = 15; $VAR12 = 18; $VAR13 = 7; $VAR14 = 6; $VAR15 = 15; $VAR16 = 2; $VAR17 = 21; $VAR18 = 13; $VAR19 = 21; $VAR20 = 20;

Author Z-Score-Based P-Values
$VAR1 = '0.212603169016528'; $VAR2 = '1.64520268046979e-07'; $VAR3 = '0.0555914674985049';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.792719203339607'; $VAR2 = '6.13435709461513e-07'; $VAR3 = '0.207280183224684';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.707531861683391'; $VAR3 = 17; $VAR4 = '0.292468138316609';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.6875
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 3996
$VAR1 = 45; $VAR2 = 23; $VAR3 = 72; $VAR4 = 209; $VAR5 = 111; $VAR6 = 41; $VAR7 = 21; $VAR8 = 38; $VAR9 = 25; $VAR10 = 38; $VAR11 = 12; $VAR12 = 20; $VAR13 = 7; $VAR14 = 2; $VAR15 = 8; $VAR16 = 10; $VAR17 = 17; $VAR18 = 8; $VAR19 = 29; $VAR20 = 26;

Author Z-Score-Based P-Values
$VAR1 = '0.193185255450597'; $VAR2 = '6.51680555251843e-05'; $VAR3 = '0.120036602904404';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.616639819605712'; $VAR2 = '0.000208013897900097'; $VAR3 = '0.383152166496388';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.708278986118095'; $VAR3 = 17; $VAR4 = '0.291721013881905';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0429447852760736
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.958823529411765

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 3724
$VAR1 = 28; $VAR2 = 28; $VAR3 = 68; $VAR4 = 145; $VAR5 = 114; $VAR6 = 46; $VAR7 = 21; $VAR8 = 50; $VAR9 = 24; $VAR10 = 58; $VAR11 = 35; $VAR12 = 17; $VAR13 = 8; $VAR14 = 1; $VAR15 = 1; $VAR16 = 3; $VAR17 = 10; $VAR18 = 9; $VAR19 = 12; $VAR20 = 14;

Author Z-Score-Based P-Values
$VAR1 = '0.124199012067483'; $VAR2 = '1.13611435836288e-05'; $VAR3 = '0.0503926742603953';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.711322132494754'; $VAR2 = '6.50684151746305e-05'; $VAR3 = '0.288612799090071';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.688986967639172'; $VAR3 = 17; $VAR4 = '0.311013032360828';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0444444444444444
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.957446808510638

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 3840
$VAR1 = 59; $VAR2 = 24; $VAR3 = 68; $VAR4 = 200; $VAR5 = 100; $VAR6 = 30; $VAR7 = 26; $VAR8 = 37; $VAR9 = 31; $VAR10 = 50; $VAR11 = 20; $VAR12 = 8; $VAR13 = 12; $VAR14 = 4; $VAR15 = 7; $VAR16 = 7; $VAR17 = 29; $VAR18 = 7; $VAR19 = 23; $VAR20 = 25;

Author Z-Score-Based P-Values
$VAR1 = '0.194073179787595'; $VAR2 = '0.00420529955617584'; $VAR3 = '0.120780428689163';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.608267548410097'; $VAR2 = '0.0131803232892083'; $VAR3 = '0.378552128300695';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.698841682120609'; $VAR3 = 26; $VAR4 = '0.301158317879391';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0340909090909091
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.967032967032967

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 3975
$VAR1 = 59; $VAR2 = 38; $VAR3 = 84; $VAR4 = 210; $VAR5 = 78; $VAR6 = 29; $VAR7 = 32; $VAR8 = 44; $VAR9 = 26; $VAR10 = 31; $VAR11 = 22; $VAR12 = 31; $VAR13 = 27; $VAR14 = 4; $VAR15 = 10; $VAR16 = 8; $VAR17 = 12; $VAR18 = 6; $VAR19 = 30; $VAR20 = 20;

Author Z-Score-Based P-Values
$VAR1 = '0.162228019092045'; $VAR2 = '2.82089423963558e-05'; $VAR3 = '0.0481828262236582';
Excellent match. Z-Score-Based P-Value > 0.10.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.770902623868835'; $VAR2 = '0.000134048038258897'; $VAR3 = '0.228963328092906';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.395961015806038'; $VAR3 = 26; $VAR4 = '0.604038984193962';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.0426829268292683
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.95906432748538

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.125
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.888888888888889
testsize: 3977
$VAR1 = 56; $VAR2 = 63; $VAR3 = 186; $VAR4 = 190; $VAR5 = 119; $VAR6 = 59; $VAR7 = 24; $VAR8 = 45; $VAR9 = 25; $VAR10 = 32; $VAR11 = 38; $VAR12 = 22; $VAR13 = 23; $VAR14 = 0; $VAR15 = 8; $VAR16 = 3; $VAR17 = 19; $VAR18 = 6; $VAR19 = 31; $VAR20 = 14;

Author Z-Score-Based P-Values
$VAR1 = '0.0423976423672781'; $VAR2 = '2.01443177752622e-09'; $VAR3 = '0.0158584135957354';
Poor match. Z-Score-Based P-Value < 0.05.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.727780832401894'; $VAR2 = '3.45789235911935e-08'; $VAR3 = '0.272219133019183';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.584450175531671'; $VAR3 = 25; $VAR4 = '0.415549824468329';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0423 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0423 Test, Z-Score-Based Method
0.323170731707317
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.755760368663594

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0423 Test, Z-Score-Based Method
0.166666666666667
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
0.857142857142857

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0423 Test, Z-Score-Based Method
0.5
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.666666666666667
testsize: 3604
$VAR1 = 59; $VAR2 = 46; $VAR3 = 149; $VAR4 = 186; $VAR5 = 161; $VAR6 = 70; $VAR7 = 18; $VAR8 = 43; $VAR9 = 28; $VAR10 = 28; $VAR11 = 10; $VAR12 = 20; $VAR13 = 23; $VAR14 = 1; $VAR15 = 2; $VAR16 = 8; $VAR17 = 5; $VAR18 = 9; $VAR19 = 17; $VAR20 = 11;

Author Z-Score-Based P-Values
$VAR1 = '0.0658926213372214'; $VAR2 = '5.21551986928024e-08'; $VAR3 = '0.00381386579447849';
Good match. Z-Score-Based P-Value > 0.05.

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.945286080923056'; $VAR2 = '7.48210988902229e-07'; $VAR3 = '0.054713170865955';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.639572952956511'; $VAR3 = 17; $VAR4 = '0.360427047043489';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0658 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0658 Test, Z-Score-Based Method
0.236842105263158
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.808510638297872

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0658 Test, Z-Score-Based Method
0.428571428571429
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
0.7

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0658 Test, Z-Score-Based Method
0.222222222222222
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
0.818181818181818
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Peter Kirby » Mon Jun 01, 2015 5:40 pm

I was able to get two samples from "Who Is the Rich Man Who Will Be Saved?"

I used the 20-word list again, with the text representing the candidate 'Clement' being an amalgam of the 'Protrepticus', 'Paedagogus', and 'Stromata'.

Once again, the quotes were stripped out of Clement's text.

Both results indicated 'Clement' as the author, whether compared to the other author candidates or when including the controls.
testsize: 2253
$VAR1 = 37; $VAR2 = 27; $VAR3 = 34; $VAR4 = 158; $VAR5 = 45; $VAR6 = 25; $VAR7 = 18; $VAR8 = 16; $VAR9 = 17; $VAR10 = 13; $VAR11 = 9; $VAR12 = 13; $VAR13 = 6; $VAR14 = 3; $VAR15 = 8; $VAR16 = 3; $VAR17 = 5; $VAR18 = 2; $VAR19 = 12; $VAR20 = 12;

20 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'DE', 'D' ]; $VAR6 = [ 'MEN' ]; $VAR7 = [ 'ALLA', 'ALL' ]; $VAR8 = [ 'GAR' ]; $VAR9 = [ 'EIS' ]; $VAR10 = [ 'EN' ]; $VAR11 = [ 'EK', 'EC' ]; $VAR12 = [ 'PROS' ]; $VAR13 = [ 'OUN' ]; $VAR14 = [ 'INA' ]; $VAR15 = [ 'OTI' ]; $VAR16 = [ 'APO', 'AP' ]; $VAR17 = [ 'PERI' ]; $VAR18 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR19 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR20 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.208196292919809'; $VAR2 = '0.0932345475188718'; $VAR3 = '0.141470247032426';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0214522218181445'; $VAR2 = '0.0103085972758034'; $VAR3 = '0.134132570397203'; $VAR4 = '0.140652936434049'; $VAR5 = '0.0511905598787918'; $VAR6 = '1.59789692301995e-09'; $VAR7 = '0.000185454070684451'; $VAR8 = '5.86839538861128e-11'; $VAR9 = '2.71800067855554e-21'; $VAR10 = '2.59426813855879e-14'; $VAR11 = '0.0463151380944977'; $VAR12 = '1.18980310995731e-11'; $VAR13 = '0.0103361900539986'; $VAR14 = '0.0209995586927314'; $VAR15 = '0.0518370483156715'; $VAR16 = '0.071164782895655'; $VAR17 = '0.0990672447909065'; $VAR18 = '0.00426014523990597'; $VAR19 = '0.00814453672161491'; $VAR20 = '0.000264497475569051'; $VAR21 = '0.000118873639053934'; $VAR22 = '0.0037462059321022'; $VAR23 = '0.0495702877660622'; $VAR24 = '0.0177602567824573'; $VAR25 = '0.116773705407625'; $VAR26 = '0.183043669103362'; $VAR27 = '0.00111946173790666'; $VAR28 = '0.128641438721505'; $VAR29 = '0.138066701734825';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.470074016093697'; $VAR2 = '0.210508734695654'; $VAR3 = '0.319417249210649';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.532144752911203'; $VAR3 = 26; $VAR4 = '0.467855247088797';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.672413793103448
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
1

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 2271
$VAR1 = 26; $VAR2 = 30; $VAR3 = 45; $VAR4 = 157; $VAR5 = 49; $VAR6 = 14; $VAR7 = 20; $VAR8 = 18; $VAR9 = 18; $VAR10 = 14; $VAR11 = 9; $VAR12 = 12; $VAR13 = 5; $VAR14 = 4; $VAR15 = 3; $VAR16 = 4; $VAR17 = 5; $VAR18 = 4; $VAR19 = 13; $VAR20 = 17;

20 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'DE', 'D' ]; $VAR6 = [ 'MEN' ]; $VAR7 = [ 'ALLA', 'ALL' ]; $VAR8 = [ 'GAR' ]; $VAR9 = [ 'EIS' ]; $VAR10 = [ 'EN' ]; $VAR11 = [ 'EK', 'EC' ]; $VAR12 = [ 'PROS' ]; $VAR13 = [ 'OUN' ]; $VAR14 = [ 'INA' ]; $VAR15 = [ 'OTI' ]; $VAR16 = [ 'APO', 'AP' ]; $VAR17 = [ 'PERI' ]; $VAR18 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR19 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR20 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.204236844917481'; $VAR2 = '0.101315350171642'; $VAR3 = '0.119210191241955';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.0437695554976908'; $VAR2 = '0.0146604225777152'; $VAR3 = '0.153054092037539'; $VAR4 = '0.153039500232093'; $VAR5 = '0.031531571879505'; $VAR6 = '4.29180498184385e-07'; $VAR7 = '0.000551005430101909'; $VAR8 = '1.41194773821056e-11'; $VAR9 = '4.56862160694218e-14'; $VAR10 = '1.18935696183293e-11'; $VAR11 = '0.0754097190754827'; $VAR12 = '2.06455017149327e-09'; $VAR13 = '0.0183870653250492'; $VAR14 = '0.0184862258854074'; $VAR15 = '0.0623516509396925'; $VAR16 = '0.0573902447922814'; $VAR17 = '0.0770965026209377'; $VAR18 = '0.000505910956908204'; $VAR19 = '0.00280242051987883'; $VAR20 = '8.60831546448997e-05'; $VAR21 = '0.000124683833344049'; $VAR22 = '0.00283388373572017'; $VAR23 = '0.0371750648758543'; $VAR24 = '0.0372141758870239'; $VAR25 = '0.0867163365653205'; $VAR26 = '0.14063890885387'; $VAR27 = '0.000396502732872027'; $VAR28 = '0.116793399137818'; $VAR29 = '0.0850763122816903';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.480826107701284'; $VAR2 = '0.238522414959484'; $VAR3 = '0.280651477339232';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.571626156146223'; $VAR3 = 3; $VAR4 = '0.428373843853777';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.719298245614035
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.00325732899022801
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.995491932932616

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
1

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Tenorikuma
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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Tenorikuma » Mon Jun 01, 2015 5:42 pm

Good stuff!

Meanwhile, an unruly mob stands outside Peter's house, chanting "Letter to Theodore! Letter to Theodore!"

:)

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Re: Clement of Alexandria -- A Basic Stylometric Study

Post by Peter Kirby » Mon Jun 01, 2015 5:54 pm

I was able to get two samples from "Excerpts from Theodotus."

I used the 20-word list again, with the text representing the candidate 'Clement' being an amalgam of the 'Protrepticus', 'Paedagogus', and 'Stromata'.

Once again, the quotes were stripped out of Clement's text.

Both results indicated 'Clement' as the author, whether compared to the other author candidates or when including the controls.
testsize: 3121
$VAR1 = 50; $VAR2 = 5; $VAR3 = 72; $VAR4 = 203; $VAR5 = 86; $VAR6 = 27; $VAR7 = 25; $VAR8 = 25; $VAR9 = 27; $VAR10 = 46; $VAR11 = 14; $VAR12 = 8; $VAR13 = 17; $VAR14 = 7; $VAR15 = 11; $VAR16 = 18; $VAR17 = 1; $VAR18 = 1; $VAR19 = 11; $VAR20 = 15;

20 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'DE', 'D' ]; $VAR6 = [ 'MEN' ]; $VAR7 = [ 'ALLA', 'ALL' ]; $VAR8 = [ 'GAR' ]; $VAR9 = [ 'EIS' ]; $VAR10 = [ 'EN' ]; $VAR11 = [ 'EK', 'EC' ]; $VAR12 = [ 'PROS' ]; $VAR13 = [ 'OUN' ]; $VAR14 = [ 'INA' ]; $VAR15 = [ 'OTI' ]; $VAR16 = [ 'APO', 'AP' ]; $VAR17 = [ 'PERI' ]; $VAR18 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR19 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR20 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.10885162952729'; $VAR2 = '0.0186738140689081'; $VAR3 = '0.0269436422750085';
Excellent match. Z-Score-Based P-Value > 0.10.

Control Z-Score-Based P-Values
$VAR1 = '0.00179352712776704'; $VAR2 = '0.000666010584230304'; $VAR3 = '0.0891224916413988'; $VAR4 = '0.0949112635234201'; $VAR5 = '0.0013572062824009'; $VAR6 = '2.36341190055549e-13'; $VAR7 = '1.62814481658228e-06'; $VAR8 = '3.67268267820245e-14'; $VAR9 = '1.05852539970194e-207'; $VAR10 = '6.4956942026233e-26'; $VAR11 = '6.87728190025473e-06'; $VAR12 = '3.75862527550106e-15'; $VAR13 = '3.14056613344782e-08'; $VAR14 = '0.000306994450920009'; $VAR15 = '0.00313028112518066'; $VAR16 = '0.00965555329251112'; $VAR17 = '0.0567736792156081'; $VAR18 = '2.86525940434905e-07'; $VAR19 = '0.000224616419806748'; $VAR20 = '3.0398644728735e-11'; $VAR21 = '2.0523568683947e-09'; $VAR22 = '1.03058477128963e-05'; $VAR23 = '0.0109220297280939'; $VAR24 = '0.00147694019208987'; $VAR25 = '0.0147378187985948'; $VAR26 = '0.0714852966346017'; $VAR27 = '1.38888190252536e-08'; $VAR28 = '0.037218123810885'; $VAR29 = '0.0119218677604037';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.704682292339377'; $VAR2 = '0.120890299593525'; $VAR3 = '0.174427408067098';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.534207322528544'; $VAR3 = 4; $VAR4 = '0.465792677471456';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.975609756097561
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.146788990825688
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.869218500797448

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0.125
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
0.886426592797784

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.1 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
testsize: 3237
$VAR1 = 66; $VAR2 = 11; $VAR3 = 64; $VAR4 = 205; $VAR5 = 90; $VAR6 = 35; $VAR7 = 28; $VAR8 = 30; $VAR9 = 39; $VAR10 = 30; $VAR11 = 20; $VAR12 = 9; $VAR13 = 25; $VAR14 = 14; $VAR15 = 7; $VAR16 = 16; $VAR17 = 8; $VAR18 = 5; $VAR19 = 13; $VAR20 = 14;

20 Words
$VAR1 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR2 = [ 'TIS', 'TINOS', 'TINI', 'TINA', 'TINES', 'TINWN', 'TISI', 'TISIN', 'TINAS', 'TI', 'TINA' ]; $VAR3 = [ 'EIMI', 'EI', 'ESTI', 'ESTIN', 'ESMEN', 'ESTE', 'EISI', 'EISIN', 'HN', 'HSQA', 'HN', 'HMEN', 'HTE', 'HSAN', 'ESOMAI', 'ESHi', 'ESEI', 'ESTAI', 'ESOMEQA', 'ESESQE', 'ESONTAI', 'W', 'HiS', 'Hi', 'WMEN', 'HTE', 'WSI', 'EIHN', 'EIHS', 'EIH', 'EIHMEN', 'EIMEN', 'EIHTE', 'EITE', 'EIHSAN', 'EIEN', 'ESOIMHN', 'ESOIO', 'ESOITO', 'ESOIMEQA', 'ESOISQE', 'ESOINTO', 'ISQI', 'ESTW', 'ESTE', 'ESTWN', 'ONTWN', 'ESTWSAN', 'EINAI', 'ESESQAI', 'WN', 'OUSA', 'ON', 'ESOMENOS', 'ESOMENH', 'ESOMENON' ]; $VAR4 = [ 'KAI' ]; $VAR5 = [ 'DE', 'D' ]; $VAR6 = [ 'MEN' ]; $VAR7 = [ 'ALLA', 'ALL' ]; $VAR8 = [ 'GAR' ]; $VAR9 = [ 'EIS' ]; $VAR10 = [ 'EN' ]; $VAR11 = [ 'EK', 'EC' ]; $VAR12 = [ 'PROS' ]; $VAR13 = [ 'OUN' ]; $VAR14 = [ 'INA' ]; $VAR15 = [ 'OTI' ]; $VAR16 = [ 'APO', 'AP' ]; $VAR17 = [ 'PERI' ]; $VAR18 = [ 'POLUS', 'POLLOU', 'POLLWi', 'POLUN', 'POLLH', 'POLLHS', 'POLLHi', 'POLLHN', 'POLU', 'POLLOU', 'POLLWi', 'POLU', 'POLLOI', 'POLLWN', 'POLLOIS', 'POLLOUS', 'POLLAI', 'POLLWN', 'POLLAIS', 'POLLAS', 'POLLA', 'POLLWN', 'POLLOIS', 'POLLA' ]; $VAR19 = [ 'PAS', 'PANTOS', 'PANTI', 'PANTA', 'PAS', 'PASA', 'PASHS', 'PASHi', 'PASAN', 'PASA', 'PAN', 'PANTOS', 'PANTI', 'PAN', 'PANTES', 'PANTWN', 'PASI', 'PASIN', 'PANTAS', 'PANTES', 'PASAI', 'PASWN', 'PASAIS', 'PASAS', 'PASAI', 'PANTA', 'PANTWN' ]; $VAR20 = [ 'EPI', 'EP' ];

Author Z-Score-Based P-Values
$VAR1 = '0.0891341862316561'; $VAR2 = '0.00823999538657703'; $VAR3 = '0.0093546013832856';
Good match. Z-Score-Based P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '0.000328542255805407'; $VAR2 = '0.000375126445316027'; $VAR3 = '0.0509940396182017'; $VAR4 = '0.0334067353761326'; $VAR5 = '0.00109430330190708'; $VAR6 = '1.01384699562633e-13'; $VAR7 = '7.05465265857593e-07'; $VAR8 = '6.29986959432625e-27'; $VAR9 = '2.20548917518569e-205'; $VAR10 = '6.07961232653377e-34'; $VAR11 = '5.17333453177403e-06'; $VAR12 = '5.26642442579496e-23'; $VAR13 = '4.22245726650285e-05'; $VAR14 = '0.000190587658762553'; $VAR15 = '0.00180764696312585'; $VAR16 = '0.00752207890136413'; $VAR17 = '0.0187845375392933'; $VAR18 = '1.37400598951698e-07'; $VAR19 = '8.17174001200763e-05'; $VAR20 = '7.40283815826768e-13'; $VAR21 = '3.26476640497917e-14'; $VAR22 = '1.29858151574643e-06'; $VAR23 = '0.00717195042654787'; $VAR24 = '0.000533604322258993'; $VAR25 = '0.0108024584041673'; $VAR26 = '0.0476589981929109'; $VAR27 = '9.16778250469167e-16'; $VAR28 = '0.0369309775796127'; $VAR29 = '0.0115383763038494';

Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.835146656084214'; $VAR2 = '0.0772049971417717'; $VAR3 = '0.0876483467740139';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.636090164498051'; $VAR3 = 3; $VAR4 = '0.363909835501949';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0891 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0891 Test, Z-Score-Based Method
0.175355450236967
Posterior Probability of a Sample Meeting the Test Being by the Best Author Candidate (with Prior = 0.5), not Any Other, Z-Score-Based Method
0.850806451612903

Percentage of Samples in the Second-Best Author Candidate that Meet the P-Value>0.0891 Test, Z-Score-Based Method
0.125
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Second-Best Author, Z-Score-Based Method
0.888888888888889

Percentage of Samples in the Best Control Candidate that Meet the P-Value>0.0891 Test, Z-Score-Based Method
0
Posterior Probability of a Sample Meeting the Test Being by the Best Author, not the Best Control Author, Z-Score-Based Method
1
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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