Origen -- A Basic Stylometric Study

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Peter Kirby
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Re: Origen -- A Basic Stylometric Study

Post by Peter Kirby » Fri Jun 05, 2015 10:55 pm

It does not seem that a reliable result can be obtained for the 'Fragmenta in librum primum Regnorum (in catenis)', at 1865 words, either.

(The phrasing of the program, such as 'Good' and "Decent', may perhaps need to be further adjusted, particularly on account of the 'testsize'. How bad that situation really is will need to be determined empirically.)

(For that matter, the idea that any of these numbers is actually a 'posterior probability' needs to be contradicted; they aren't, really. Just figures arrived at using the equations, treating certain things in a certain way, for the purposes of arriving at comparisons. Probability estimates should be based on data.)
testsize: 1865


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.251416241002533'; $VAR2 = '0.244365665829986'; $VAR3 = '0.263424860072452'; $VAR4 = '0.24079323309503';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.4460078489874'; $VAR3 = 25; $VAR4 = '0.5539921510126';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.17 Test, Z-Score-Based Method
0.914285714285714
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.17 Test, Z-Score-Based Method
0.0780952380952381
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
0.921305182341651

Author Z-Score-Based P-Values
$VAR1 = '0.162480158620052'; $VAR2 = '0.157923656749568'; $VAR3 = '0.170240843942161'; $VAR4 = '0.155614937809533';
Good compatibility. Z-Score-Based P-Value > 0.15.
Decent indicator. 18.1% of the rest have P-Value > 0.15.

Control Z-Score-Based P-Values
$VAR1 = '4.45960034483123e-05'; $VAR2 = '0.00474527883133966'; $VAR3 = '8.31245056296586e-05'; $VAR4 = '1.6360045670979e-05'; $VAR5 = '1.15798466313763e-10'; $VAR6 = '0.0416658150025683'; $VAR7 = '2.77245593300341e-07'; $VAR8 = '0.0024850407670454'; $VAR9 = '0.00334699488127056'; $VAR10 = '0.0176111285654208'; $VAR11 = '0.0318670264211295'; $VAR12 = '0.114465750759549'; $VAR13 = '0.00133107269115731'; $VAR14 = '0.00819075274704703'; $VAR15 = '0.000606730543937574'; $VAR16 = '0.000811018217690464'; $VAR17 = '0.0196827592481145'; $VAR18 = '0.0348586734284918'; $VAR19 = '0.0396126840787309'; $VAR20 = '0.0435039394207646'; $VAR21 = '0.064012868528842'; $VAR22 = '0.00193556583459673'; $VAR23 = '0.00669187820645381'; $VAR24 = '0.00662838528628678'; $VAR25 = '0.211458366797447'; $VAR26 = '0.120977519268692'; $VAR27 = '0.162954613848735'; $VAR28 = '0.0958731909323333'; $VAR29 = '0.0416232343714149'; $VAR30 = '0.180837528269577';
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Re: Origen -- A Basic Stylometric Study

Post by MrMacSon » Fri Jun 05, 2015 11:04 pm

Peter Kirby wrote:Clement of Alexandria has been moved from 'control' to 'author candidate' (control #31 takes the place that Clement had as control #25 and becomes author candidate #3), and Cyril of Alexandria has been added as an author candidate (#4). Clement of Alexandria is represented by his 'trilogy' (Protrepticus, Paedagogus, and Stromata--without quotations). Cyril of Alexandria is represented by 'Against Julian' and his 'Commentary on John' (without quotations).

Four samples are taken from the text 'Fragmenta in Lamentationes (in catenis)', each approximately 2000 words long. This appears to have a continuous source, which is some 'catena'. The quotations were removed first. Among the four author candidates, 'Origen' is picked as the most likely for the first sample, while 'Clement of Alexandria' is picked as the most likely for the other three samples. This is sufficient to reject the (null) hypothesis that Origen may have authored the entire thing. One possibility is that this was written by Clement of Alexandria. Another possibility is that a text written by Clement of Alexandria was extensively used and adapted by Origen.
Interesting. It seems Clement left Alexandria about the time Origen supposedly revived the Catechetical School of Alexandria ie. 202/3

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Re: Origen -- A Basic Stylometric Study

Post by Stephan Huller » Fri Jun 05, 2015 11:55 pm

FWIW Both Clement and Origen are credited with writing "Stromata" in 7 and 10 books respectively. I also wonder about a reference in Quis Dives S to a work which sounds suspiciously similar to De Principiis (from bed). Their relationship is curious. Something strange going on

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Re: Origen -- A Basic Stylometric Study

Post by Peter Kirby » Fri Jun 05, 2015 11:58 pm

Stephan Huller wrote:Their relationship is curious. Something strange going on
Well, just as long as there's no "naked man with naked man"... :shh:

I hear some scholarship is saying Origen never really neutered himself; it was another guy by the same name.
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Re: Origen -- A Basic Stylometric Study

Post by Peter Kirby » Sat Jun 06, 2015 12:13 am

Seriously, though, we can't read stylometry results "mystically." (And we really got to stop asking what explicitly-stated non-results "mean." ;) )

If the null hypothesis is rejected, and if Origen is not the author (or can't be shown to be the author), there are at least four possibilities:

(1) Origen is still just a partial author.
(2) This other guy (with the best score) is a partial/full author.
(3) None of the candidates plugged into the machine is the author; the author is at large.
(4) Fluke error not in Origen's favor (surprise, he's the author after all, but style tested much differently because fill-in-the-excuse).

Now, between (2) and (3), it might be exciting if a particular other author is getting a lot of "hits" for the second best / sometimes the best authorship. Someone might think this clearly points to (2), that the other guy is the author.

But, in my experience working with this technique so far, this is very common in all cases. What it comes down to is the brute fact of where the averages are. If two authors have averages that are more near to each other, then the other author is going to be the "second" (and sometimes the "first") inordinately frequently. Some of the other guys just have averages that are so different that they are not going to be the 'fallback guy' when the primary author under consideration isn't picked (this is particularly true when it is the primary author's work--there tends to be someone or several 'shadowing' the primary author when the sample is obviously the primary author's--...but of course it's not true if you throw in some Oscar Wilde or something).

In English, we might just say that they have similar styles. I have observed casually that this 'lineage' of authors--Clement, Origen, and Eusebius--frequently compete with each other for similarity of style. It looks like Cyril of Alexandria does too, as well as Basil of Caesarea. This could be due to any number of common factors: regional, educational, or even personal on some level, with each author immersing himself in the previous one's work and paying it homage subconsciously when producing original work.

So we shouldn't get too excited that Clement (or whomever) is popping up instead of Origen. Yes, it is more of an indication against Origen than it is one for Clement (as Ben C. Smith astutely commented/inquired). Making a positive case for the identity of the author, with non-conventional/non-attributional authorship, is very delicate (partly due to the much lower prior probability than the attributed author) and requires careful work. I haven't even started on that part of it really. So I don't know. The stylometry giveth, but not as much as we'd liketh.
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Re: Origen -- A Basic Stylometric Study

Post by Peter Kirby » Sat Jun 06, 2015 12:44 am

The 'Fragmenta in Lucam (in catenis)' is a tough nut to crack. If divided into two samples of 6000 words each, it goes to Cyril of Alexandria (once) and then Clement of Alexandria (once). If divided into three samples of 4000 words each, it goes to Cyril of Alexandira (once), Origen (once), and Clement of Alexandria (once). If divided into four samples of 3000 words each, it goes to Cyril of Alexandria (once), Origen (twice), and Clement of Alexandria (once). If divided into six samples of 2000 words each, it goes to Cyril of Alexandria (twice), a control (once), Origen (twice), and Clement of Alexandria (once). A bit mind boggling, right? Makes you want to understand it, right? To tease through and figure out what it means? Well, good luck. Even starting from 12,000 words, there may sometimes be no very definite results, despite how tantalizing it is to 'make a guess' for our pattern-seeking minds (yes, I am guilty of this also). If I had to make a guess, none of these three men were the author at all (or maybe Origen was after all), but we can't be sure of that either.

Two samples of 6000 words each.
testsize: 5908


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.185382666646521'; $VAR2 = '0.136019269977811'; $VAR3 = '0.296832246944354'; $VAR4 = '0.381765816431314';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 4; $VAR2 = '0.735821949393893'; $VAR3 = 25; $VAR4 = '0.264178050606107';

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
0.0548780487804878
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
0.947976878612717

Author Z-Score-Based P-Values
$VAR1 = '0.0511953040518964'; $VAR2 = '0.0375631012834053'; $VAR3 = '0.0819732362772601'; $VAR4 = '0.105428503119379';
Good compatibility. Z-Score-Based P-Value > 0.1.
Excellent indicator. 0% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '1.00000000000001e-99'; $VAR2 = '1.43183755710957e-24'; $VAR3 = '0'; $VAR4 = '1.00000000000001e-99'; $VAR5 = '0'; $VAR6 = '3.70785250492421e-07'; $VAR7 = '5.73731492790154e-26'; $VAR8 = '6.16754243820852e-42'; $VAR9 = '1.45080375819387e-11'; $VAR10 = '6.88237529780679e-08'; $VAR11 = '3.75320975561194e-05'; $VAR12 = '0.00198845437883358'; $VAR13 = '0'; $VAR14 = '1.06041670927342e-14'; $VAR15 = '3.08166100947634e-28'; $VAR16 = '3.47837571807287e-18'; $VAR17 = '1.69635557832634e-07'; $VAR18 = '0.000757183188625988'; $VAR19 = '4.1364107560568e-12'; $VAR20 = '2.61820950943241e-08'; $VAR21 = '0.00255556769122658'; $VAR22 = '3.22947993262929e-09'; $VAR23 = '5.25627581513217e-05'; $VAR24 = '7.32833289074245e-08'; $VAR25 = '0.0378514074707061'; $VAR26 = '0.0253331779506385'; $VAR27 = '0.000199917403087781'; $VAR28 = '0.0102555696133697'; $VAR29 = '0.000297009597603721'; $VAR30 = '0.0329694270498855';
testsize: 6035


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.261737104700918'; $VAR2 = '0.131903224103111'; $VAR3 = '0.413510220888985'; $VAR4 = '0.192849450306987';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.768738208050387'; $VAR3 = 30; $VAR4 = '0.231261791949613';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.033112582781457
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
0.967948717948718

Author Z-Score-Based P-Values
$VAR1 = '0.0852655847076296'; $VAR2 = '0.0429698553471232'; $VAR3 = '0.134708415938845'; $VAR4 = '0.0628241882623397';
Good compatibility. Z-Score-Based P-Value > 0.1.
Excellent indicator. 0% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '0'; $VAR2 = '3.94846205979452e-72'; $VAR3 = '0'; $VAR4 = '1.00000000000001e-99'; $VAR5 = '0'; $VAR6 = '2.06396802442247e-07'; $VAR7 = '4.98646807055177e-19'; $VAR8 = '0'; $VAR9 = '2.88027172282021e-08'; $VAR10 = '1.31117347102372e-08'; $VAR11 = '0.000134294826176203'; $VAR12 = '0.00497780374011198'; $VAR13 = '0'; $VAR14 = '8.74490685306601e-13'; $VAR15 = '1.76718377310382e-55'; $VAR16 = '1.29232548263151e-22'; $VAR17 = '2.96514578411458e-09'; $VAR18 = '0.00151984067075444'; $VAR19 = '2.35876817092908e-14'; $VAR20 = '2.391542955436e-10'; $VAR21 = '0.00151301001912683'; $VAR22 = '9.29871294108155e-11'; $VAR23 = '0.000490018041541458'; $VAR24 = '2.52795942585364e-10'; $VAR25 = '0.0371030511697181'; $VAR26 = '0.0140499260952557'; $VAR27 = '0.00156635055875104'; $VAR28 = '0.00213117980584769'; $VAR29 = '4.76954082374279e-05'; $VAR30 = '0.0405247317415363';
Three samples of 4000 words each.
testsize: 3905


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.20898170949919'; $VAR2 = '0.185239040160985'; $VAR3 = '0.266893894507018'; $VAR4 = '0.338885355832807';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 4; $VAR2 = '0.637729652278011'; $VAR3 = 25; $VAR4 = '0.362270347721989';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.14 Test, Z-Score-Based Method
0.888888888888889
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.14 Test, Z-Score-Based Method
0.046875
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
0.949907235621521

Author Z-Score-Based P-Values
$VAR1 = '0.0873301713287291'; $VAR2 = '0.0774084830332523'; $VAR3 = '0.111530763097619'; $VAR4 = '0.141614863121746';
Good compatibility. Z-Score-Based P-Value > 0.1.
Great indicator. 3% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '6.72975116180032e-32'; $VAR2 = '8.87375819330738e-12'; $VAR3 = '8.28471221686373e-281'; $VAR4 = '5.07706314688111e-214'; $VAR5 = '2.04803832801197e-73'; $VAR6 = '0.00272997556068388'; $VAR7 = '9.71857258240474e-18'; $VAR8 = '1.88093528440952e-06'; $VAR9 = '4.43868266790089e-06'; $VAR10 = '0.000714127254640474'; $VAR11 = '0.00399230134496908'; $VAR12 = '0.0383022208190227'; $VAR13 = '2.83394830742764e-92'; $VAR14 = '1.18960133580849e-05'; $VAR15 = '1.44138524107698e-06'; $VAR16 = '3.44080751201954e-10'; $VAR17 = '5.52789863484954e-05'; $VAR18 = '0.00373732204917662'; $VAR19 = '8.14623685610456e-05'; $VAR20 = '0.0172006746980358'; $VAR21 = '0.0304089170059398'; $VAR22 = '2.73692065303206e-06'; $VAR23 = '0.00132369208250008'; $VAR24 = '2.34942227008608e-07'; $VAR25 = '0.0804461036466781'; $VAR26 = '0.0455516238697948'; $VAR27 = '0.00628757715978969'; $VAR28 = '0.0285564650722439'; $VAR29 = '0.00697181072183627'; $VAR30 = '0.0764042118853678';
testsize: 4238


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.269372269945217'; $VAR2 = '0.217007223780397'; $VAR3 = '0.248536531924002'; $VAR4 = '0.265083974350384';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.565301345217532'; $VAR3 = 25; $VAR4 = '0.434698654782468';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.12 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.12 Test, Z-Score-Based Method
0.0765765765765766
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
0.928870292887029

Author Z-Score-Based P-Values
$VAR1 = '0.129552796277235'; $VAR2 = '0.104368176645754'; $VAR3 = '0.119531987068859'; $VAR4 = '0.127490369117651';
Good compatibility. Z-Score-Based P-Value > 0.1.
Good indicator. 9% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '3.39287738998242e-19'; $VAR2 = '1.16275385549245e-06'; $VAR3 = '5.45408291836279e-225'; $VAR4 = '9.60080611556913e-185'; $VAR5 = '2.33179615105599e-64'; $VAR6 = '0.0014505166631294'; $VAR7 = '4.22737077142718e-13'; $VAR8 = '2.49345517086457e-22'; $VAR9 = '0.000964143579701891'; $VAR10 = '0.00259054393235648'; $VAR11 = '0.00107801406768794'; $VAR12 = '0.0169140115345313'; $VAR13 = '5.59242087756628e-26'; $VAR14 = '5.93296690736944e-05'; $VAR15 = '6.03310145356642e-07'; $VAR16 = '2.79880725056262e-10'; $VAR17 = '3.14690919571736e-05'; $VAR18 = '0.0116031339833592'; $VAR19 = '0.000143322980115507'; $VAR20 = '0.0106594108802873'; $VAR21 = '0.0132428035811677'; $VAR22 = '4.2184707001035e-06'; $VAR23 = '0.00360318706328447'; $VAR24 = '0.000203378167435642'; $VAR25 = '0.0996219569287428'; $VAR26 = '0.0809085606460844'; $VAR27 = '0.0237573417410134'; $VAR28 = '0.0557530594179128'; $VAR29 = '0.0028820900845385'; $VAR30 = '0.0668375364845194';
testsize: 3800


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.252525409740514'; $VAR2 = '0.19572260526902'; $VAR3 = '0.361889564873791'; $VAR4 = '0.189862420116676';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.698509036299953'; $VAR3 = 25; $VAR4 = '0.301490963700047';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.12 Test, Z-Score-Based Method
0.970588235294118
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.12 Test, Z-Score-Based Method
0.104
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
0.903218743157434

Author Z-Score-Based P-Values
$VAR1 = '0.0866056778467016'; $VAR2 = '0.0671246862510342'; $VAR3 = '0.124113019373964'; $VAR4 = '0.065114887284873';
Good compatibility. Z-Score-Based P-Value > 0.1.
Excellent indicator. 0% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '1.00986906903767e-69'; $VAR2 = '3.76810351574468e-07'; $VAR3 = '1.32556666122325e-296'; $VAR4 = '1.05085473177218e-211'; $VAR5 = '3.62153208136847e-57'; $VAR6 = '0.0120351539994841'; $VAR7 = '2.01893283740734e-14'; $VAR8 = '1.91374757046561e-05'; $VAR9 = '8.12248534040698e-05'; $VAR10 = '0.000523818288529229'; $VAR11 = '0.00268547140123833'; $VAR12 = '0.0196746271466033'; $VAR13 = '2.70679646594278e-11'; $VAR14 = '7.75519889221911e-05'; $VAR15 = '9.9293353480369e-11'; $VAR16 = '1.72755616499367e-14'; $VAR17 = '9.16386530045978e-06'; $VAR18 = '0.0151319534969297'; $VAR19 = '2.26029718940449e-05'; $VAR20 = '0.00464140975674224'; $VAR21 = '0.0211843233962859'; $VAR22 = '1.47258992768634e-09'; $VAR23 = '0.00109437562661067'; $VAR24 = '1.97833779512875e-05'; $VAR25 = '0.053569749100154'; $VAR26 = '0.0366500929705032'; $VAR27 = '0.0416389320028535'; $VAR28 = '0.00926112926893515'; $VAR29 = '0.000649943505765448'; $VAR30 = '0.0502407418933347';
Four samples of 3000 words each.
testsize: 2967


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.194479885393011'; $VAR2 = '0.151536599303969'; $VAR3 = '0.276518913794353'; $VAR4 = '0.377464601508667';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 4; $VAR2 = '0.621823655361088'; $VAR3 = 25; $VAR4 = '0.378176344638912';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.15 Test, Z-Score-Based Method
0.916666666666667
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.15 Test, Z-Score-Based Method
0.0231884057971014
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
0.97532767925983

Author Z-Score-Based P-Values
$VAR1 = '0.082173485558334'; $VAR2 = '0.0640286810602534'; $VAR3 = '0.11683739386913'; $VAR4 = '0.159489923177265';
Good compatibility. Z-Score-Based P-Value > 0.15.
Excellent indicator. 0% of the rest have P-Value > 0.15.

Control Z-Score-Based P-Values
$VAR1 = '4.8317788346258e-09'; $VAR2 = '6.0795251199758e-06'; $VAR3 = '8.67933096112499e-17'; $VAR4 = '5.95234528650495e-118'; $VAR5 = '1.81317057553444e-21'; $VAR6 = '0.0237518610305606'; $VAR7 = '5.82782762552829e-07'; $VAR8 = '0.000256857561358988'; $VAR9 = '0.000497861791258364'; $VAR10 = '0.00300339809660911'; $VAR11 = '0.0160806067335386'; $VAR12 = '0.030182689323158'; $VAR13 = '3.71765741305838e-08'; $VAR14 = '0.000673219068510006'; $VAR15 = '4.57871265830793e-05'; $VAR16 = '2.42119518081158e-06'; $VAR17 = '0.00171077122369616'; $VAR18 = '0.0134861770155975'; $VAR19 = '0.000762823955186937'; $VAR20 = '0.0281517427590441'; $VAR21 = '0.0270806947422293'; $VAR22 = '0.00014173578156693'; $VAR23 = '0.0016494955401905'; $VAR24 = '0.000987640072858896'; $VAR25 = '0.0969974616338688'; $VAR26 = '0.0507364040408672'; $VAR27 = '0.0390401528106693'; $VAR28 = '0.0567899166682633'; $VAR29 = '0.0151400215742713'; $VAR30 = '0.0829273533373128';
testsize: 2941


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.272597470338474'; $VAR2 = '0.215128609045311'; $VAR3 = '0.244749663345735'; $VAR4 = '0.26752425727048';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.539505114504389'; $VAR3 = 25; $VAR4 = '0.460494885495611';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.14 Test, Z-Score-Based Method
0.959183673469388
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.14 Test, Z-Score-Based Method
0.0835913312693498
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
0.919837615123606

Author Z-Score-Based P-Values
$VAR1 = '0.144718620436155'; $VAR2 = '0.114209113821671'; $VAR3 = '0.12993456464445'; $VAR4 = '0.142025314458417';
Good compatibility. Z-Score-Based P-Value > 0.1.
Decent indicator. 18.1% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '5.48630607906107e-09'; $VAR2 = '2.13263168423182e-05'; $VAR3 = '5.13303526446958e-14'; $VAR4 = '7.56058243337933e-97'; $VAR5 = '3.89738936128087e-28'; $VAR6 = '0.0180680086794945'; $VAR7 = '2.54834767565217e-08'; $VAR8 = '0.000187429525099505'; $VAR9 = '0.000940035019018488'; $VAR10 = '0.00512064894229043'; $VAR11 = '0.0100107385152369'; $VAR12 = '0.033916970247986'; $VAR13 = '1.47879710818001e-05'; $VAR14 = '0.0010881744980114'; $VAR15 = '1.53281070353707e-05'; $VAR16 = '1.88387314562688e-06'; $VAR17 = '0.000671462646636144'; $VAR18 = '0.0140807741281647'; $VAR19 = '0.000315714673991303'; $VAR20 = '0.0178280991436529'; $VAR21 = '0.0361759922322783'; $VAR22 = '0.00016100145860915'; $VAR23 = '0.00594873782745028'; $VAR24 = '0.00258105189142409'; $VAR25 = '0.123524657607834'; $VAR26 = '0.1127543169802'; $VAR27 = '0.0472678705956151'; $VAR28 = '0.119998803828237'; $VAR29 = '0.022878017326915'; $VAR30 = '0.079163066130514';
testsize: 2999


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.283381613190368'; $VAR2 = '0.232361976857254'; $VAR3 = '0.260784662926582'; $VAR4 = '0.223471747025797';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.541836216409267'; $VAR3 = 25; $VAR4 = '0.458163783590733';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.18 Test, Z-Score-Based Method
0.833333333333333
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.18 Test, Z-Score-Based Method
0.0626959247648903
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
0.93002915451895

Author Z-Score-Based P-Values
$VAR1 = '0.18494585815316'; $VAR2 = '0.151648459927287'; $VAR3 = '0.170198209880819'; $VAR4 = '0.145846350302578';
Good compatibility. Z-Score-Based P-Value > 0.15.
Good indicator. 9% of the rest have P-Value > 0.15.

Control Z-Score-Based P-Values
$VAR1 = '7.73022227371144e-08'; $VAR2 = '6.96173697360355e-05'; $VAR3 = '3.19243548927891e-21'; $VAR4 = '7.57757519308008e-110'; $VAR5 = '1.11716121027927e-16'; $VAR6 = '0.0200210479471521'; $VAR7 = '8.19427794828948e-08'; $VAR8 = '0.000125504839109134'; $VAR9 = '0.00157434701885888'; $VAR10 = '0.00341984357738752'; $VAR11 = '0.0141546764494911'; $VAR12 = '0.0507116259108012'; $VAR13 = '3.73554265176125e-07'; $VAR14 = '0.00180802049024286'; $VAR15 = '6.61812703729968e-05'; $VAR16 = '1.96530489221583e-06'; $VAR17 = '0.00484245535339492'; $VAR18 = '0.0380134102942493'; $VAR19 = '0.000208543197196631'; $VAR20 = '0.0137197091275381'; $VAR21 = '0.0555999275666311'; $VAR22 = '0.00108454050578989'; $VAR23 = '0.0183817502624493'; $VAR24 = '0.00354355733286601'; $VAR25 = '0.156385807306176'; $VAR26 = '0.0762040699273255'; $VAR27 = '0.106434340316533'; $VAR28 = '0.0565319394412148'; $VAR29 = '0.0310619229760629'; $VAR30 = '0.1286352134089';
testsize: 3036


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.256689564926926'; $VAR2 = '0.189228165532317'; $VAR3 = '0.33352847982719'; $VAR4 = '0.220553789713566';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.594047772035181'; $VAR3 = 27; $VAR4 = '0.405952227964819';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.953488372093023
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.128526645768025
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
0.88121546961326

Author Z-Score-Based P-Values
$VAR1 = '0.102098117672716'; $VAR2 = '0.0752653872665632'; $VAR3 = '0.132660749143786'; $VAR4 = '0.0877251351520643';
Good compatibility. Z-Score-Based P-Value > 0.1.
Great indicator. 3% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '8.61296654489458e-08'; $VAR2 = '1.76762458952608e-05'; $VAR3 = '2.56918886138801e-10'; $VAR4 = '5.54398085194279e-182'; $VAR5 = '6.49645485968137e-21'; $VAR6 = '0.012318598783147'; $VAR7 = '1.20312861728234e-08'; $VAR8 = '2.29481179261931e-05'; $VAR9 = '0.000923660458986704'; $VAR10 = '0.00243506451286401'; $VAR11 = '0.00244804518209135'; $VAR12 = '0.04779993378003'; $VAR13 = '3.61417874065214e-07'; $VAR14 = '0.000103152281971991'; $VAR15 = '1.91056099263044e-10'; $VAR16 = '6.16880096208411e-16'; $VAR17 = '1.9031731392956e-07'; $VAR18 = '0.0189922507351938'; $VAR19 = '0.00120000520417682'; $VAR20 = '0.00601697798782469'; $VAR21 = '0.0257064128694697'; $VAR22 = '8.08040781264898e-08'; $VAR23 = '0.00292130165499855'; $VAR24 = '0.00195520816251634'; $VAR25 = '0.0711400235886941'; $VAR26 = '0.0461218104564744'; $VAR27 = '0.0906558852900007'; $VAR28 = '0.0360540343892244'; $VAR29 = '0.00293326363630396'; $VAR30 = '0.0761501871142933';
Six samples of 2000 words each.
testsize: 1979


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.216037843971584'; $VAR2 = '0.189172132484873'; $VAR3 = '0.27227229347429'; $VAR4 = '0.322517730069252';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 4; $VAR2 = '0.548459926445913'; $VAR3 = 25; $VAR4 = '0.451540073554087';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.17 Test, Z-Score-Based Method
0.837837837837838
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.17 Test, Z-Score-Based Method
0.0248091603053435
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
0.971240657698057

Author Z-Score-Based P-Values
$VAR1 = '0.117568403991634'; $VAR2 = '0.10294800802986'; $VAR3 = '0.148171350011827'; $VAR4 = '0.175515058316514';
Good compatibility. Z-Score-Based P-Value > 0.15.
Excellent indicator. 0% of the rest have P-Value > 0.15.

Control Z-Score-Based P-Values
$VAR1 = '5.62806509830497e-05'; $VAR2 = '0.000532592111257889'; $VAR3 = '6.72855925931029e-05'; $VAR4 = '1.4657116122486e-05'; $VAR5 = '2.49713433594539e-15'; $VAR6 = '0.044373156368264'; $VAR7 = '3.01165352561948e-06'; $VAR8 = '0.0024548802092393'; $VAR9 = '0.00135716052780752'; $VAR10 = '0.00690180941866696'; $VAR11 = '0.0205984066969119'; $VAR12 = '0.0699152367979993'; $VAR13 = '0.000406139441991884'; $VAR14 = '0.00436890949406101'; $VAR15 = '0.000838128120815964'; $VAR16 = '4.6573325744078e-05'; $VAR17 = '0.00776770679514699'; $VAR18 = '0.0259458382979663'; $VAR19 = '0.0123393191683948'; $VAR20 = '0.055562908837608'; $VAR21 = '0.0426677623073781'; $VAR22 = '0.00157004326316051'; $VAR23 = '0.00766774613510617'; $VAR24 = '0.00466847526462705'; $VAR25 = '0.144499312567195'; $VAR26 = '0.0836574148720515'; $VAR27 = '0.0837398670769635'; $VAR28 = '0.0693186901085937'; $VAR29 = '0.0336188827942499'; $VAR30 = '0.130295688733247';
testsize: 1954


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.247538839849786'; $VAR2 = '0.233742946439479'; $VAR3 = '0.235455237712872'; $VAR4 = '0.283262975997863';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 4; $VAR2 = '0.53432703304649'; $VAR3 = 30; $VAR4 = '0.46567296695351';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.14 Test, Z-Score-Based Method
0.891891891891892
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.14 Test, Z-Score-Based Method
0.118421052631579
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
0.882787750791975

Author Z-Score-Based P-Values
$VAR1 = '0.127395356210426'; $VAR2 = '0.120295327963086'; $VAR3 = '0.121176555154917'; $VAR4 = '0.145780709606506';
Good compatibility. Z-Score-Based P-Value > 0.1.
Poor indicator. 21.2% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '3.5667610215914e-06'; $VAR2 = '0.000587254534200603'; $VAR3 = '0.000104274621518347'; $VAR4 = '6.07299243588095e-08'; $VAR5 = '8.81546058659828e-14'; $VAR6 = '0.0295397820604302'; $VAR7 = '4.13224285586655e-08'; $VAR8 = '0.00160683555679105'; $VAR9 = '0.00510024283902371'; $VAR10 = '0.0304814864724164'; $VAR11 = '0.0372431174565386'; $VAR12 = '0.103602463214885'; $VAR13 = '0.00234817883080327'; $VAR14 = '0.00703848072902847'; $VAR15 = '0.000990176661413576'; $VAR16 = '0.000864653073844719'; $VAR17 = '0.0113204579296359'; $VAR18 = '0.0363320788898315'; $VAR19 = '0.00968412781427666'; $VAR20 = '0.0738016928514325'; $VAR21 = '0.0836457665527032'; $VAR22 = '0.00235864149234664'; $VAR23 = '0.0247267478409212'; $VAR24 = '0.00785316991425345'; $VAR25 = '0.101810895965296'; $VAR26 = '0.0831868010299255'; $VAR27 = '0.0718163879937068'; $VAR28 = '0.10674188580544'; $VAR29 = '0.0583161745672116'; $VAR30 = '0.127049786682126';
testsize: 1964


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.259849824806734'; $VAR2 = '0.229850920613986'; $VAR3 = '0.239509213399196'; $VAR4 = '0.270790041180084';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 4; $VAR2 = '0.498660430398835'; $VAR3 = 26; $VAR4 = '0.501339569601165';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.14 Test, Z-Score-Based Method
0.945945945945946
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.14 Test, Z-Score-Based Method
0.111531190926276
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
0.894530872548072

Author Z-Score-Based P-Values
$VAR1 = '0.140508618736654'; $VAR2 = '0.124287308620816'; $VAR3 = '0.129509838132288'; $VAR4 = '0.146424322903254';
Good compatibility. Z-Score-Based P-Value > 0.1.
Decent indicator. 18.1% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '0.0008215424896047'; $VAR2 = '0.00317308475321171'; $VAR3 = '0.00280126361725984'; $VAR4 = '0.00349623763319514'; $VAR5 = '1.68947314291647e-09'; $VAR6 = '0.0638460834371779'; $VAR7 = '8.71402777225954e-05'; $VAR8 = '0.00261705840924445'; $VAR9 = '0.00235433407387312'; $VAR10 = '0.0138926000992659'; $VAR11 = '0.0232837859658977'; $VAR12 = '0.0498453612159327'; $VAR13 = '0.00135714899834258'; $VAR14 = '0.0039744435690622'; $VAR15 = '0.00029132457606385'; $VAR16 = '0.00012635367002735'; $VAR17 = '0.00439068929956047'; $VAR18 = '0.0362567656574647'; $VAR19 = '0.0159931268081539'; $VAR20 = '0.0440410043589898'; $VAR21 = '0.0601649072205556'; $VAR22 = '0.00104028167017381'; $VAR23 = '0.0261150395798459'; $VAR24 = '0.0159995582106808'; $VAR25 = '0.129357002500167'; $VAR26 = '0.14721101284244'; $VAR27 = '0.0747316179693251'; $VAR28 = '0.14349745239945'; $VAR29 = '0.0345172156008187'; $VAR30 = '0.0983608556548548';
testsize: 1996


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.271760394839182'; $VAR2 = '0.252857381992377'; $VAR3 = '0.237176695767386'; $VAR4 = '0.238205527401055';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.503376919424863'; $VAR3 = 25; $VAR4 = '0.496623080575138';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.694444444444444
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.2 Test, Z-Score-Based Method
0.0477178423236514
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
0.935704301910234

Author Z-Score-Based P-Values
$VAR1 = '0.205669265398356'; $VAR2 = '0.191363395816739'; $VAR3 = '0.179496194862956'; $VAR4 = '0.180274818423761';
Excellent compatibility. Z-Score-Based P-Value > 0.2.
Great indicator. 3% of the rest have P-Value > 0.2.

Control Z-Score-Based P-Values
$VAR1 = '0.000153387562905137'; $VAR2 = '0.00208167297562764'; $VAR3 = '7.79098751130336e-05'; $VAR4 = '4.69665740782276e-08'; $VAR5 = '7.43704918028294e-13'; $VAR6 = '0.0678351143260547'; $VAR7 = '4.36406182506718e-06'; $VAR8 = '0.00125159282184915'; $VAR9 = '0.0109098025819893'; $VAR10 = '0.0202062819875546'; $VAR11 = '0.0378252009609091'; $VAR12 = '0.128703668435761'; $VAR13 = '0.00358466329244103'; $VAR14 = '0.00745594066714921'; $VAR15 = '0.00139096164732777'; $VAR16 = '0.000437588358900622'; $VAR17 = '0.0243569720795278'; $VAR18 = '0.056119347512182'; $VAR19 = '0.0282540137061275'; $VAR20 = '0.0817351745813'; $VAR21 = '0.0903871339440536'; $VAR22 = '0.00607311902230898'; $VAR23 = '0.0341604157221575'; $VAR24 = '0.018136975892191'; $VAR25 = '0.202909788312222'; $VAR26 = '0.113870929858592'; $VAR27 = '0.149615956804335'; $VAR28 = '0.114464261938489'; $VAR29 = '0.0723238185486703'; $VAR30 = '0.175434234239054';
testsize: 1977


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.306870348297829'; $VAR2 = '0.255622755085737'; $VAR3 = '0.252709532132445'; $VAR4 = '0.184797364483989';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.533623097543078'; $VAR3 = 27; $VAR4 = '0.466376902456922';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.16 Test, Z-Score-Based Method
0.931506849315068
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.16 Test, Z-Score-Based Method
0.0737704918032787
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
0.926616776499497

Author Z-Score-Based P-Values
$VAR1 = '0.164480686057504'; $VAR2 = '0.137012280142508'; $VAR3 = '0.135450809923395'; $VAR4 = '0.0990502909797102';
Good compatibility. Z-Score-Based P-Value > 0.15.
Excellent indicator. 0% of the rest have P-Value > 0.15.

Control Z-Score-Based P-Values
$VAR1 = '7.77246023461926e-05'; $VAR2 = '0.000379980016489236'; $VAR3 = '2.22566108532725e-06'; $VAR4 = '4.59729918318504e-08'; $VAR5 = '7.6174983268226e-12'; $VAR6 = '0.0349924608155837'; $VAR7 = '4.41276623063637e-06'; $VAR8 = '0.00702077107862547'; $VAR9 = '0.00271690784784973'; $VAR10 = '0.00460626251843917'; $VAR11 = '0.0238380377406323'; $VAR12 = '0.0628284126368144'; $VAR13 = '0.00347453531039989'; $VAR14 = '0.00478930751185507'; $VAR15 = '0.00114643107784862'; $VAR16 = '2.57756704492611e-05'; $VAR17 = '0.0112499500587998'; $VAR18 = '0.065020590122983'; $VAR19 = '0.0425090576184769'; $VAR20 = '0.0483633311995723'; $VAR21 = '0.0747075433407808'; $VAR22 = '0.00665914479030914'; $VAR23 = '0.020054522841974'; $VAR24 = '0.0167334642543525'; $VAR25 = '0.0937705962976218'; $VAR26 = '0.0884080112388436'; $VAR27 = '0.14375313443267'; $VAR28 = '0.0511195196171825'; $VAR29 = '0.028512017635614'; $VAR30 = '0.074304525073366';
testsize: 2073


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.237223574130833'; $VAR2 = '0.206622090204217'; $VAR3 = '0.331290785482297'; $VAR4 = '0.224863550182654';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.559247554862608'; $VAR3 = 30; $VAR4 = '0.440752445137392';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.16 Test, Z-Score-Based Method
0.936507936507937
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.16 Test, Z-Score-Based Method
0.0694736842105263
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
0.930939410045177

Author Z-Score-Based P-Values
$VAR1 = '0.120826376916072'; $VAR2 = '0.105239956196059'; $VAR3 = '0.168738142750641'; $VAR4 = '0.114530978502461';
Good compatibility. Z-Score-Based P-Value > 0.15.
Excellent indicator. 0% of the rest have P-Value > 0.15.

Control Z-Score-Based P-Values
$VAR1 = '0.000317655332560772'; $VAR2 = '0.0018527462769627'; $VAR3 = '7.0718334293009e-17'; $VAR4 = '2.88893269607474e-07'; $VAR5 = '1.13907750999041e-12'; $VAR6 = '0.0270045188639169'; $VAR7 = '4.32481190038632e-05'; $VAR8 = '0.00310966374248065'; $VAR9 = '0.00958640578752158'; $VAR10 = '0.0170649493522634'; $VAR11 = '0.0282614378988947'; $VAR12 = '0.101333197107517'; $VAR13 = '0.00421722232892421'; $VAR14 = '0.00179329877601146'; $VAR15 = '6.80305749723535e-09'; $VAR16 = '5.14696778794051e-07'; $VAR17 = '2.87365012927176e-06'; $VAR18 = '0.043662001970894'; $VAR19 = '0.0115137275120768'; $VAR20 = '0.0297901004438511'; $VAR21 = '0.045756463041517'; $VAR22 = '5.12667490309465e-07'; $VAR23 = '0.0174552706740458'; $VAR24 = '0.00914908938527714'; $VAR25 = '0.106562589163146'; $VAR26 = '0.066589680770981'; $VAR27 = '0.118442408466962'; $VAR28 = '0.0552929860287518'; $VAR29 = '0.016242867055358'; $VAR30 = '0.132985380729216';
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Peter Kirby
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Re: Origen -- A Basic Stylometric Study

Post by Peter Kirby » Sat Jun 06, 2015 1:51 pm

The 'In Jesu Nave homiliae xxvi (fragmenta e catenis)' measures 3138 words, after quotations are removed. The best candidate selected for authorship is Clement of Alexandria, and the second-best candidate is Origen. With only one sample from which to get a reading, these results are inconclusive. The text may have been written by Clement of Alexandria, by Origen, or by a third party.
testsize: 3138


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.259641338253233'; $VAR2 = '0.180472585449325'; $VAR3 = '0.306600844719609'; $VAR4 = '0.253285231577833';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.592105516976304'; $VAR3 = 25; $VAR4 = '0.407894483023697';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.975609756097561
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.108196721311475
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
0.900169704124548

Author Z-Score-Based P-Values
$VAR1 = '0.113538412556111'; $VAR2 = '0.0789187538458483'; $VAR3 = '0.134073308326101'; $VAR4 = '0.110758954297202';
Good compatibility. Z-Score-Based P-Value > 0.1.
Good indicator. 6% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '2.49992810578324e-09'; $VAR2 = '2.29343905083564e-10'; $VAR3 = '1.20758229785341e-08'; $VAR4 = '2.16134018634608e-130'; $VAR5 = '3.37321365081711e-25'; $VAR6 = '0.014105254305146'; $VAR7 = '2.28902521026368e-09'; $VAR8 = '7.14601540409744e-05'; $VAR9 = '0.00689000864317602'; $VAR10 = '0.00598129661414424'; $VAR11 = '0.00732240873963437'; $VAR12 = '0.0641609188544345'; $VAR13 = '4.48744547439564e-07'; $VAR14 = '0.000535994099575872'; $VAR15 = '0.000471075390559681'; $VAR16 = '6.34424846837246e-07'; $VAR17 = '0.00543382559687069'; $VAR18 = '0.033055788095653'; $VAR19 = '0.000923044504097955'; $VAR20 = '0.0154480955582398'; $VAR21 = '0.08125619242638'; $VAR22 = '0.00214922599011719'; $VAR23 = '0.00495397581472666'; $VAR24 = '0.00172679698301192'; $VAR25 = '0.0923615153363624'; $VAR26 = '0.0454975224563873'; $VAR27 = '0.0507442853065628'; $VAR28 = '0.0349268630082531'; $VAR29 = '0.00683620278593274'; $VAR30 = '0.0601899304980839';


33 Words
$VAR1 = [ 'O', 'OI', 'H', 'AI', 'TO', 'TA' ]; $VAR2 = [ 'TOU', 'TWN', 'THS' ]; $VAR3 = [ 'TWi', 'TOIS', 'THi', 'TAIS' ]; $VAR4 = [ 'TON', 'TOUS', 'THN', 'TAS', 'TO', 'TA' ]; $VAR5 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR6 = [ 'OUTOS', 'TOUTOU', 'TOUTWi', 'TOUTON', 'AUTOI', 'TOUTWN', 'TOUTOIS', 'TOUTOUS', 'AUTH', 'TAUTHS', 'TAUTHi', 'TAUTHN', 'AUTAI', 'TAUTAIS', 'TAUTAS', 'TOUTO', 'TOUTO', 'TAUTA' ]; $VAR7 = [ 'ODE', 'TOUDE', 'TWiDE', 'TONDE', 'OIDE', 'TWNDE', 'TOISDE', 'TOUSDE', 'HDE', 'THSDE', 'THiDE', 'THNDE', 'AIDE', 'TWNDE', 'TAISDE', 'TASDE', 'TODE', 'TOUDE', 'TODE', 'TADE' ]; $VAR8 = [ 'EKEINOS', 'EKEINOU', 'EKEINWi', 'EKEINON', 'EKEINOI', 'EKEINWN', 'EKEINOIS', 'EKEINOUS', 'EKEINH', 'EKEINHS', 'EKEINHi', 'EKEINHN', 'EKEINAI', 'EKEINAIS', 'EKEINAS', 'EKEINO', 'EKEINOU', 'EKEINWi', 'EKEINO', 'EKEINA', 'EKEINWN', 'EKEINOIS', 'EKEINA' ]; $VAR9 = [ 'DH' ]; $VAR10 = [ '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' ]; $VAR11 = [ 'LEGW', 'LEGEIS', 'LEGEI', 'LEGETON', 'LEGETON', 'LEGOMEN', 'LEGETE', 'LEGOUSI', 'LEGOUSIN', 'LEGW', 'LEGHiS', 'LEGHi', 'LEGHTON', 'LEGHTON', 'LEGWMEN', 'LEGHTE', 'LEGWSI', 'LEGWSIN', 'LEGOIMI', 'LEGOIS', 'LEGOI', 'LEGOITON', 'LEGOITHN', 'LEGOIMEN', 'LEGOITE', 'LEGOIEN', 'LEGE', 'LEGETW', 'LEGETON', 'LEGETWN', 'LEGETE', 'LEGONTWN', 'LEGOMAI', 'LEGEI', 'LEGHi', 'LEGETAI', 'LEGESQON', 'LEGESQON', 'LEGOMEQA', 'LEGESQE', 'LEGONTAI', 'LEGWMAI', 'LEGHi', 'LEGHTAI', 'LEGHSQON', 'LEGHSQON', 'LEGWMEQA', 'LEGHSQE', 'LEGWNTAI', 'LEGOIMHN', 'LEGOIO', 'LEGOITO', 'LEGOISQON', 'LEGOISQHN', 'LEGOIMEQA', 'LEGOISQE', 'LEGOINTO', 'LEGOU', 'LEGESQW', 'LEGESQON', 'LEGESQWN', 'LEGESQE', 'LEGESQWN', 'LEGEIN', 'LEGESQAI', 'LEGWN', 'LEGOUSA', 'LEGON', 'LEGOMENOS', 'LEGOMENH', 'LEGOMENON', 'ELEGON', 'ELEGOMHN', 'ELEGON', 'ELEGES', 'ELEGE', 'ELEGETON', 'ELEGETHN', 'ELEGOMEN', 'ELEGETE', 'ELEGON', 'ELEGOU', 'ELEGETO', 'ELEGESQON', 'ELEGESQHN', 'ELEGOMEQA', 'ELEGESQE', 'ELEGONTO', 'LECW', 'LECOMAI', 'LEXQHSOMAI', 'LECW', 'LECEIS', 'LECEI', 'LECETON', 'LECETON', 'LECOMEN', 'LECETE', 'LECOUSI', 'LECOUSIN', 'LECOIMI' ]; $VAR12 = [ 'KAI', 'KA' ]; $VAR13 = [ 'TE', 'T' ]; $VAR14 = [ 'OUTE', 'OUT', 'OUQ', 'EITE', 'EIT', 'EIQ', 'MHTE', 'MHT', 'MHQ' ]; $VAR15 = [ 'DE', 'D' ]; $VAR16 = [ 'MH' ]; $VAR17 = [ 'META', 'MET', 'MEQ', 'ME', 'M' ]; $VAR18 = [ 'MEN' ]; $VAR19 = [ 'ALLA', 'ALL' ]; $VAR20 = [ 'GAR' ]; $VAR21 = [ 'EIS' ]; $VAR22 = [ 'EPI', 'EP' ]; $VAR23 = [ 'DIA', 'DI' ]; $VAR24 = [ 'EK', 'EC' ]; $VAR25 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR26 = [ 'OUDE', 'OUD', 'MHDE', 'MHD' ]; $VAR27 = [ 'OUN' ]; $VAR28 = [ 'EPEI' ]; $VAR29 = [ 'OTI', 'OT', 'OQ' ]; $VAR30 = [ 'OUN' ]; $VAR31 = [ 'PERI' ]; $VAR32 = [ 'GIGNOMAI', 'GIGNWMAI', 'GIGNOIMHN', 'GIGESQAI', 'EGIGNOMHN', 'GENHSOMAI', 'GENHSOIMEHN', 'GENHQHSOMAI', 'GENHQHSOIMHN', 'GENHSESQAI', 'GENHSOMENOS', 'GENHSOMENH', 'GENHSOMENON', 'GEGONA', 'GEGONWS', 'GEGONW', 'GEGONWS', 'GEGONW', 'GEGONWS', 'GEGONOIMI', 'GEGONOIHN', 'GEGENHMAI', 'GEGENHMAI', 'GEGENHMENOS', 'GEGONENAI', 'GEGONWS', 'GEGONUIA', 'GEGONOS', 'EGEGONEIN', 'EGEGONH', 'EGEGENHMHN', 'GIGNEI', 'GIGNHi', 'GIGNOIO', 'GIGNOU', 'EGIGNOU', 'GENHSEI', 'GENHSHi', 'GENHSOIO', 'GENHQHSEI', 'GENHQHSHi', 'GENHQHSOIO', 'EGENOU', 'GENHi', 'GENOIO', 'GENOU', 'EGENHQHS', 'GENHQHiS', 'GENHQEIHS', 'GENHQHTI', 'GEGONAS', 'GEGONWS', 'GEGONHS', 'GEGONWS', 'GEGONOIS', 'GEGONOIHS', 'GEGONWS', 'GEGENHSAI', 'GEGENHMENOS', 'GEGENHSO', 'EGEGONEIS', 'EGEGONHS', 'EGEGENHSO', 'GIGNETAI', 'GIGNHTAI', 'GIGNOITO', 'GIGNESQW', 'EGIGNETO', 'GENHSETAI', 'GENHSOITO', 'GENHQHSETAI', 'GENHQHSOITO', 'EGENETO', 'GENHTAI', 'GENOITO', 'GENESQW', 'EGENHQH', 'GENHQHi', 'GENHQEIN', 'GENHQHTW', 'GEGONE', 'GEGONWS', 'GEGONHi', 'GEGONWS', 'GEGONOI', 'GEGONOIN', 'GEGONWS', 'GEGENHTAI', 'GE' ]; $VAR33 = [ 'AN', 'EAN' ];

$VAR1 = 198; $VAR2 = 170; $VAR3 = 58; $VAR4 = 186; $VAR5 = 27; $VAR6 = 34; $VAR7 = 2; $VAR8 = 5; $VAR9 = 2; $VAR10 = 67; $VAR11 = 9; $VAR12 = 185; $VAR13 = 13; $VAR14 = 5; $VAR15 = 89; $VAR16 = 21; $VAR17 = 17; $VAR18 = 15; $VAR19 = 19; $VAR20 = 53; $VAR21 = 9; $VAR22 = 23; $VAR23 = 14; $VAR24 = 12; $VAR25 = 30; $VAR26 = 4; $VAR27 = 13; $VAR28 = 7; $VAR29 = 14; $VAR30 = 13; $VAR31 = 19; $VAR32 = 10; $VAR33 = 14;
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Peter Kirby
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Re: Origen -- A Basic Stylometric Study

Post by Peter Kirby » Sat Jun 06, 2015 2:11 pm

The 'Libri x in Canticum canticorum (fragmenta)' measures 2688 words, before quotations are removed, and 1829 words, after quotations are removed. Clement of Alexandria is selected as the best candidate before quotations are removed and as the second-best candidate (just behind one of the controls) after quotations are removed. Because only one sample can be tested, it is not very conclusive. The text may have been written by Clement of Alexandria, by Origen, or by a third party.
testsize: 2688


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.225851992784786'; $VAR2 = '0.17660867575219'; $VAR3 = '0.358997265849387'; $VAR4 = '0.238542065613637';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.505605147641951'; $VAR3 = 27; $VAR4 = '0.494394852358049';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.12 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.12 Test, Z-Score-Based Method
0.20891364902507
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
0.827188940092166

Author Z-Score-Based P-Values
$VAR1 = '0.0783177721526614'; $VAR2 = '0.0612418684342686'; $VAR3 = '0.124488014135046'; $VAR4 = '0.0827182568247525';
Good compatibility. Z-Score-Based P-Value > 0.1.
Great indicator. 3% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '9.66925752126278e-05'; $VAR2 = '1.50188301969565e-06'; $VAR3 = '7.04398689472108e-11'; $VAR4 = '4.58779931763687e-125'; $VAR5 = '1.15245176144199e-20'; $VAR6 = '0.0393671169560113'; $VAR7 = '1.64918524982669e-06'; $VAR8 = '0.0025290312554701'; $VAR9 = '0.0130384261794336'; $VAR10 = '0.0454052221030889'; $VAR11 = '0.0125043214305692'; $VAR12 = '0.0414904333392273'; $VAR13 = '3.48125782506867e-05'; $VAR14 = '0.00596278964796469'; $VAR15 = '0.000130423507505234'; $VAR16 = '0.000184840939068934'; $VAR17 = '0.00496318501680768'; $VAR18 = '0.026219020855577'; $VAR19 = '4.37293160813715e-05'; $VAR20 = '0.0120112472906444'; $VAR21 = '0.0409319829042755'; $VAR22 = '0.000324972290238198'; $VAR23 = '0.0296569796799244'; $VAR24 = '0.0080719184776973'; $VAR25 = '0.0980574344475473'; $VAR26 = '0.0933237221361745'; $VAR27 = '0.121727861465974'; $VAR28 = '0.035013237637554'; $VAR29 = '0.00941009802891599'; $VAR30 = '0.0893374754986423';


33 Words
$VAR1 = [ 'O', 'OI', 'H', 'AI', 'TO', 'TA' ]; $VAR2 = [ 'TOU', 'TWN', 'THS' ]; $VAR3 = [ 'TWi', 'TOIS', 'THi', 'TAIS' ]; $VAR4 = [ 'TON', 'TOUS', 'THN', 'TAS', 'TO', 'TA' ]; $VAR5 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR6 = [ 'OUTOS', 'TOUTOU', 'TOUTWi', 'TOUTON', 'AUTOI', 'TOUTWN', 'TOUTOIS', 'TOUTOUS', 'AUTH', 'TAUTHS', 'TAUTHi', 'TAUTHN', 'AUTAI', 'TAUTAIS', 'TAUTAS', 'TOUTO', 'TOUTO', 'TAUTA' ]; $VAR7 = [ 'ODE', 'TOUDE', 'TWiDE', 'TONDE', 'OIDE', 'TWNDE', 'TOISDE', 'TOUSDE', 'HDE', 'THSDE', 'THiDE', 'THNDE', 'AIDE', 'TWNDE', 'TAISDE', 'TASDE', 'TODE', 'TOUDE', 'TODE', 'TADE' ]; $VAR8 = [ 'EKEINOS', 'EKEINOU', 'EKEINWi', 'EKEINON', 'EKEINOI', 'EKEINWN', 'EKEINOIS', 'EKEINOUS', 'EKEINH', 'EKEINHS', 'EKEINHi', 'EKEINHN', 'EKEINAI', 'EKEINAIS', 'EKEINAS', 'EKEINO', 'EKEINOU', 'EKEINWi', 'EKEINO', 'EKEINA', 'EKEINWN', 'EKEINOIS', 'EKEINA' ]; $VAR9 = [ 'DH' ]; $VAR10 = [ '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' ]; $VAR11 = [ 'LEGW', 'LEGEIS', 'LEGEI', 'LEGETON', 'LEGETON', 'LEGOMEN', 'LEGETE', 'LEGOUSI', 'LEGOUSIN', 'LEGW', 'LEGHiS', 'LEGHi', 'LEGHTON', 'LEGHTON', 'LEGWMEN', 'LEGHTE', 'LEGWSI', 'LEGWSIN', 'LEGOIMI', 'LEGOIS', 'LEGOI', 'LEGOITON', 'LEGOITHN', 'LEGOIMEN', 'LEGOITE', 'LEGOIEN', 'LEGE', 'LEGETW', 'LEGETON', 'LEGETWN', 'LEGETE', 'LEGONTWN', 'LEGOMAI', 'LEGEI', 'LEGHi', 'LEGETAI', 'LEGESQON', 'LEGESQON', 'LEGOMEQA', 'LEGESQE', 'LEGONTAI', 'LEGWMAI', 'LEGHi', 'LEGHTAI', 'LEGHSQON', 'LEGHSQON', 'LEGWMEQA', 'LEGHSQE', 'LEGWNTAI', 'LEGOIMHN', 'LEGOIO', 'LEGOITO', 'LEGOISQON', 'LEGOISQHN', 'LEGOIMEQA', 'LEGOISQE', 'LEGOINTO', 'LEGOU', 'LEGESQW', 'LEGESQON', 'LEGESQWN', 'LEGESQE', 'LEGESQWN', 'LEGEIN', 'LEGESQAI', 'LEGWN', 'LEGOUSA', 'LEGON', 'LEGOMENOS', 'LEGOMENH', 'LEGOMENON', 'ELEGON', 'ELEGOMHN', 'ELEGON', 'ELEGES', 'ELEGE', 'ELEGETON', 'ELEGETHN', 'ELEGOMEN', 'ELEGETE', 'ELEGON', 'ELEGOU', 'ELEGETO', 'ELEGESQON', 'ELEGESQHN', 'ELEGOMEQA', 'ELEGESQE', 'ELEGONTO', 'LECW', 'LECOMAI', 'LEXQHSOMAI', 'LECW', 'LECEIS', 'LECEI', 'LECETON', 'LECETON', 'LECOMEN', 'LECETE', 'LECOUSI', 'LECOUSIN', 'LECOIMI' ]; $VAR12 = [ 'KAI', 'KA' ]; $VAR13 = [ 'TE', 'T' ]; $VAR14 = [ 'OUTE', 'OUT', 'OUQ', 'EITE', 'EIT', 'EIQ', 'MHTE', 'MHT', 'MHQ' ]; $VAR15 = [ 'DE', 'D' ]; $VAR16 = [ 'MH' ]; $VAR17 = [ 'META', 'MET', 'MEQ', 'ME', 'M' ]; $VAR18 = [ 'MEN' ]; $VAR19 = [ 'ALLA', 'ALL' ]; $VAR20 = [ 'GAR' ]; $VAR21 = [ 'EIS' ]; $VAR22 = [ 'EPI', 'EP' ]; $VAR23 = [ 'DIA', 'DI' ]; $VAR24 = [ 'EK', 'EC' ]; $VAR25 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR26 = [ 'OUDE', 'OUD', 'MHDE', 'MHD' ]; $VAR27 = [ 'OUN' ]; $VAR28 = [ 'EPEI' ]; $VAR29 = [ 'OTI', 'OT', 'OQ' ]; $VAR30 = [ 'OUN' ]; $VAR31 = [ 'PERI' ]; $VAR32 = [ 'GIGNOMAI', 'GIGNWMAI', 'GIGNOIMHN', 'GIGESQAI', 'EGIGNOMHN', 'GENHSOMAI', 'GENHSOIMEHN', 'GENHQHSOMAI', 'GENHQHSOIMHN', 'GENHSESQAI', 'GENHSOMENOS', 'GENHSOMENH', 'GENHSOMENON', 'GEGONA', 'GEGONWS', 'GEGONW', 'GEGONWS', 'GEGONW', 'GEGONWS', 'GEGONOIMI', 'GEGONOIHN', 'GEGENHMAI', 'GEGENHMAI', 'GEGENHMENOS', 'GEGONENAI', 'GEGONWS', 'GEGONUIA', 'GEGONOS', 'EGEGONEIN', 'EGEGONH', 'EGEGENHMHN', 'GIGNEI', 'GIGNHi', 'GIGNOIO', 'GIGNOU', 'EGIGNOU', 'GENHSEI', 'GENHSHi', 'GENHSOIO', 'GENHQHSEI', 'GENHQHSHi', 'GENHQHSOIO', 'EGENOU', 'GENHi', 'GENOIO', 'GENOU', 'EGENHQHS', 'GENHQHiS', 'GENHQEIHS', 'GENHQHTI', 'GEGONAS', 'GEGONWS', 'GEGONHS', 'GEGONWS', 'GEGONOIS', 'GEGONOIHS', 'GEGONWS', 'GEGENHSAI', 'GEGENHMENOS', 'GEGENHSO', 'EGEGONEIS', 'EGEGONHS', 'EGEGENHSO', 'GIGNETAI', 'GIGNHTAI', 'GIGNOITO', 'GIGNESQW', 'EGIGNETO', 'GENHSETAI', 'GENHSOITO', 'GENHQHSETAI', 'GENHQHSOITO', 'EGENETO', 'GENHTAI', 'GENOITO', 'GENESQW', 'EGENHQH', 'GENHQHi', 'GENHQEIN', 'GENHQHTW', 'GEGONE', 'GEGONWS', 'GEGONHi', 'GEGONWS', 'GEGONOI', 'GEGONOIN', 'GEGONWS', 'GEGENHTAI', 'GE' ]; $VAR33 = [ 'AN', 'EAN' ];

$VAR1 = 157; $VAR2 = 173; $VAR3 = 77; $VAR4 = 139; $VAR5 = 48; $VAR6 = 33; $VAR7 = 1; $VAR8 = 5; $VAR9 = 1; $VAR10 = 46; $VAR11 = 19; $VAR12 = 113; $VAR13 = 7; $VAR14 = 3; $VAR15 = 77; $VAR16 = 11; $VAR17 = 20; $VAR18 = 12; $VAR19 = 14; $VAR20 = 28; $VAR21 = 17; $VAR22 = 17; $VAR23 = 21; $VAR24 = 13; $VAR25 = 16; $VAR26 = 3; $VAR27 = 3; $VAR28 = 4; $VAR29 = 6; $VAR30 = 3; $VAR31 = 8; $VAR32 = 3; $VAR33 = 8;
testsize: 1829


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.253799081132562'; $VAR2 = '0.216967604718143'; $VAR3 = '0.318855844276089'; $VAR4 = '0.210377469873206';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.493068364975752'; $VAR3 = 25; $VAR4 = '0.506931635024248';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.15 Test, Z-Score-Based Method
0.957746478873239
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.15 Test, Z-Score-Based Method
0.150278293135436
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
0.864372803811051

Author Z-Score-Based P-Values
$VAR1 = '0.122577381378136'; $VAR2 = '0.104788877530827'; $VAR3 = '0.153997856312425'; $VAR4 = '0.101606039087849';
Good compatibility. Z-Score-Based P-Value > 0.15.
Great indicator. 3% of the rest have P-Value > 0.15.

Control Z-Score-Based P-Values
$VAR1 = '0.00060085822788019'; $VAR2 = '0.000430524619596879'; $VAR3 = '5.83939701130646e-07'; $VAR4 = '3.02340761650752e-06'; $VAR5 = '1.18120053679257e-09'; $VAR6 = '0.0814808901412173'; $VAR7 = '1.87463139850242e-07'; $VAR8 = '0.0220351981224576'; $VAR9 = '0.00995605238866176'; $VAR10 = '0.0475745699132543'; $VAR11 = '0.0452863724934754'; $VAR12 = '0.0993933434090831'; $VAR13 = '0.0028839796292771'; $VAR14 = '0.00965563226784684'; $VAR15 = '0.00127655812589324'; $VAR16 = '0.00575248280726663'; $VAR17 = '0.0183130588093206'; $VAR18 = '0.0486488584381036'; $VAR19 = '0.0116975836905573'; $VAR20 = '0.0370561820944778'; $VAR21 = '0.0720080464616202'; $VAR22 = '0.0048291257172018'; $VAR23 = '0.0346309344129318'; $VAR24 = '0.0111288805011141'; $VAR25 = '0.158327709981'; $VAR26 = '0.0907559668168803'; $VAR27 = '0.104664834593212'; $VAR28 = '0.074933103053796'; $VAR29 = '0.0366865261503418'; $VAR30 = '0.124348207665766';


33 Words
$VAR1 = [ 'O', 'OI', 'H', 'AI', 'TO', 'TA' ]; $VAR2 = [ 'TOU', 'TWN', 'THS' ]; $VAR3 = [ 'TWi', 'TOIS', 'THi', 'TAIS' ]; $VAR4 = [ 'TON', 'TOUS', 'THN', 'TAS', 'TO', 'TA' ]; $VAR5 = [ 'AUTOS', 'AUTOU', 'AUTWi', 'AUTON', 'AUTOI', 'AUTWN', 'AUTOIS', 'AUTOUS', 'AUTH', 'AUTHS', 'AUTHi', 'AUTHN', 'AUTAI', 'AUTWN', 'AUTAIS', 'AUTAS', 'AUTO', 'AUTA' ]; $VAR6 = [ 'OUTOS', 'TOUTOU', 'TOUTWi', 'TOUTON', 'AUTOI', 'TOUTWN', 'TOUTOIS', 'TOUTOUS', 'AUTH', 'TAUTHS', 'TAUTHi', 'TAUTHN', 'AUTAI', 'TAUTAIS', 'TAUTAS', 'TOUTO', 'TOUTO', 'TAUTA' ]; $VAR7 = [ 'ODE', 'TOUDE', 'TWiDE', 'TONDE', 'OIDE', 'TWNDE', 'TOISDE', 'TOUSDE', 'HDE', 'THSDE', 'THiDE', 'THNDE', 'AIDE', 'TWNDE', 'TAISDE', 'TASDE', 'TODE', 'TOUDE', 'TODE', 'TADE' ]; $VAR8 = [ 'EKEINOS', 'EKEINOU', 'EKEINWi', 'EKEINON', 'EKEINOI', 'EKEINWN', 'EKEINOIS', 'EKEINOUS', 'EKEINH', 'EKEINHS', 'EKEINHi', 'EKEINHN', 'EKEINAI', 'EKEINAIS', 'EKEINAS', 'EKEINO', 'EKEINOU', 'EKEINWi', 'EKEINO', 'EKEINA', 'EKEINWN', 'EKEINOIS', 'EKEINA' ]; $VAR9 = [ 'DH' ]; $VAR10 = [ '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' ]; $VAR11 = [ 'LEGW', 'LEGEIS', 'LEGEI', 'LEGETON', 'LEGETON', 'LEGOMEN', 'LEGETE', 'LEGOUSI', 'LEGOUSIN', 'LEGW', 'LEGHiS', 'LEGHi', 'LEGHTON', 'LEGHTON', 'LEGWMEN', 'LEGHTE', 'LEGWSI', 'LEGWSIN', 'LEGOIMI', 'LEGOIS', 'LEGOI', 'LEGOITON', 'LEGOITHN', 'LEGOIMEN', 'LEGOITE', 'LEGOIEN', 'LEGE', 'LEGETW', 'LEGETON', 'LEGETWN', 'LEGETE', 'LEGONTWN', 'LEGOMAI', 'LEGEI', 'LEGHi', 'LEGETAI', 'LEGESQON', 'LEGESQON', 'LEGOMEQA', 'LEGESQE', 'LEGONTAI', 'LEGWMAI', 'LEGHi', 'LEGHTAI', 'LEGHSQON', 'LEGHSQON', 'LEGWMEQA', 'LEGHSQE', 'LEGWNTAI', 'LEGOIMHN', 'LEGOIO', 'LEGOITO', 'LEGOISQON', 'LEGOISQHN', 'LEGOIMEQA', 'LEGOISQE', 'LEGOINTO', 'LEGOU', 'LEGESQW', 'LEGESQON', 'LEGESQWN', 'LEGESQE', 'LEGESQWN', 'LEGEIN', 'LEGESQAI', 'LEGWN', 'LEGOUSA', 'LEGON', 'LEGOMENOS', 'LEGOMENH', 'LEGOMENON', 'ELEGON', 'ELEGOMHN', 'ELEGON', 'ELEGES', 'ELEGE', 'ELEGETON', 'ELEGETHN', 'ELEGOMEN', 'ELEGETE', 'ELEGON', 'ELEGOU', 'ELEGETO', 'ELEGESQON', 'ELEGESQHN', 'ELEGOMEQA', 'ELEGESQE', 'ELEGONTO', 'LECW', 'LECOMAI', 'LEXQHSOMAI', 'LECW', 'LECEIS', 'LECEI', 'LECETON', 'LECETON', 'LECOMEN', 'LECETE', 'LECOUSI', 'LECOUSIN', 'LECOIMI' ]; $VAR12 = [ 'KAI', 'KA' ]; $VAR13 = [ 'TE', 'T' ]; $VAR14 = [ 'OUTE', 'OUT', 'OUQ', 'EITE', 'EIT', 'EIQ', 'MHTE', 'MHT', 'MHQ' ]; $VAR15 = [ 'DE', 'D' ]; $VAR16 = [ 'MH' ]; $VAR17 = [ 'META', 'MET', 'MEQ', 'ME', 'M' ]; $VAR18 = [ 'MEN' ]; $VAR19 = [ 'ALLA', 'ALL' ]; $VAR20 = [ 'GAR' ]; $VAR21 = [ 'EIS' ]; $VAR22 = [ 'EPI', 'EP' ]; $VAR23 = [ 'DIA', 'DI' ]; $VAR24 = [ 'EK', 'EC' ]; $VAR25 = [ 'KATA', 'KAT', 'KAQ' ]; $VAR26 = [ 'OUDE', 'OUD', 'MHDE', 'MHD' ]; $VAR27 = [ 'OUN' ]; $VAR28 = [ 'EPEI' ]; $VAR29 = [ 'OTI', 'OT', 'OQ' ]; $VAR30 = [ 'OUN' ]; $VAR31 = [ 'PERI' ]; $VAR32 = [ 'GIGNOMAI', 'GIGNWMAI', 'GIGNOIMHN', 'GIGESQAI', 'EGIGNOMHN', 'GENHSOMAI', 'GENHSOIMEHN', 'GENHQHSOMAI', 'GENHQHSOIMHN', 'GENHSESQAI', 'GENHSOMENOS', 'GENHSOMENH', 'GENHSOMENON', 'GEGONA', 'GEGONWS', 'GEGONW', 'GEGONWS', 'GEGONW', 'GEGONWS', 'GEGONOIMI', 'GEGONOIHN', 'GEGENHMAI', 'GEGENHMAI', 'GEGENHMENOS', 'GEGONENAI', 'GEGONWS', 'GEGONUIA', 'GEGONOS', 'EGEGONEIN', 'EGEGONH', 'EGEGENHMHN', 'GIGNEI', 'GIGNHi', 'GIGNOIO', 'GIGNOU', 'EGIGNOU', 'GENHSEI', 'GENHSHi', 'GENHSOIO', 'GENHQHSEI', 'GENHQHSHi', 'GENHQHSOIO', 'EGENOU', 'GENHi', 'GENOIO', 'GENOU', 'EGENHQHS', 'GENHQHiS', 'GENHQEIHS', 'GENHQHTI', 'GEGONAS', 'GEGONWS', 'GEGONHS', 'GEGONWS', 'GEGONOIS', 'GEGONOIHS', 'GEGONWS', 'GEGENHSAI', 'GEGENHMENOS', 'GEGENHSO', 'EGEGONEIS', 'EGEGONHS', 'EGEGENHSO', 'GIGNETAI', 'GIGNHTAI', 'GIGNOITO', 'GIGNESQW', 'EGIGNETO', 'GENHSETAI', 'GENHSOITO', 'GENHQHSETAI', 'GENHQHSOITO', 'EGENETO', 'GENHTAI', 'GENOITO', 'GENESQW', 'EGENHQH', 'GENHQHi', 'GENHQEIN', 'GENHQHTW', 'GEGONE', 'GEGONWS', 'GEGONHi', 'GEGONWS', 'GEGONOI', 'GEGONOIN', 'GEGONWS', 'GEGENHTAI', 'GE' ]; $VAR33 = [ 'AN', 'EAN' ];

$VAR1 = 113; $VAR2 = 118; $VAR3 = 50; $VAR4 = 105; $VAR5 = 34; $VAR6 = 32; $VAR7 = 1; $VAR8 = 5; $VAR9 = 1; $VAR10 = 39; $VAR11 = 19; $VAR12 = 94; $VAR13 = 6; $VAR14 = 3; $VAR15 = 75; $VAR16 = 8; $VAR17 = 10; $VAR18 = 11; $VAR19 = 13; $VAR20 = 23; $VAR21 = 9; $VAR22 = 10; $VAR23 = 18; $VAR24 = 8; $VAR25 = 13; $VAR26 = 3; $VAR27 = 3; $VAR28 = 4; $VAR29 = 5; $VAR30 = 3; $VAR31 = 7; $VAR32 = 3; $VAR33 = 8;
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Peter Kirby
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Re: Origen -- A Basic Stylometric Study

Post by Peter Kirby » Sat Jun 06, 2015 5:06 pm

There is extant some 'Fragmenta ex commentariis in epistulam i ad Corinthios (in catenis)' that has been divided into ten samples of approximately 2300 words each. It appears to have a continuous source and represents a commentary on most of the epistle of 1 Corinthians, from chapter one to chapter sixteen. The direct quotations were removed first. Four author candidates were considered: Origen, Eusebius, Clement, and Cyril. Among the author candidates, Origen was favored 5 times, Clement was favored 4 times, and Cyril was favored 1 time. But when the thirty controls are added to the mix, one of them (Gregory Nyssenus) was selected as the closest match to the sample 8 out of 10 times (otherwise, Origen once and Clement once). This is enough to reject the hypothesis that Origen, Eusebius, Clement, or Cyril wrote it. On the basis of the stylometric evidence, the most likely conclusion appears to be that Gregory Nyssenus or some other third party wrote it; further analysis is required to determine which of these two options is more likely.
testsize: 2378


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.327846832005197'; $VAR2 = '0.279949334194057'; $VAR3 = '0.188402215064618'; $VAR4 = '0.203801618736128';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.450534057588192'; $VAR3 = 25; $VAR4 = '0.549465942411808';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.101234567901235
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
0.908071748878924

Author Z-Score-Based P-Values
$VAR1 = '0.136647699395042'; $VAR2 = '0.11668385578356'; $VAR3 = '0.0785266982512794'; $VAR4 = '0.084945223240211';
Good compatibility. Z-Score-Based P-Value > 0.1.
Good indicator. 9% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '6.24036174431989e-09'; $VAR2 = '0.0005630441376127'; $VAR3 = '5.21032778595213e-07'; $VAR4 = '1.64532257364947e-14'; $VAR5 = '2.49908977277351e-12'; $VAR6 = '0.0717974027804116'; $VAR7 = '1.97933729120857e-08'; $VAR8 = '5.23965924359914e-05'; $VAR9 = '0.0018912365702569'; $VAR10 = '0.00388059837208881'; $VAR11 = '0.00322542606535338'; $VAR12 = '0.0497741531093786'; $VAR13 = '9.29802282403964e-05'; $VAR14 = '0.000149345725744383'; $VAR15 = '0.000145235563895237'; $VAR16 = '1.4864189531235e-07'; $VAR17 = '0.0061828257630352'; $VAR18 = '0.0128412983139789'; $VAR19 = '0.0301380762218536'; $VAR20 = '0.042536784670174'; $VAR21 = '0.0305003622333354'; $VAR22 = '0.000745342014153972'; $VAR23 = '0.00421092982720129'; $VAR24 = '0.00470413456983714'; $VAR25 = '0.166653898105815'; $VAR26 = '0.0692685689420043'; $VAR27 = '0.0714527598500202'; $VAR28 = '0.0690712549212559'; $VAR29 = '0.0181138370494578'; $VAR30 = '0.102176402679442';
testsize: 2283


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.239651429977924'; $VAR2 = '0.230685802973467'; $VAR3 = '0.289587010537955'; $VAR4 = '0.240075756510654';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.503477048874307'; $VAR3 = 25; $VAR4 = '0.496522951125693';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.982456140350877
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.200934579439252
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
0.830204364392103

Author Z-Score-Based P-Values
$VAR1 = '0.108026141388581'; $VAR2 = '0.103984763081303'; $VAR3 = '0.130535283463784'; $VAR4 = '0.108217412344167';
Good compatibility. Z-Score-Based P-Value > 0.1.
Decent indicator. 12.1% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '5.1529065948624e-06'; $VAR2 = '0.000865125229834103'; $VAR3 = '1.85282139721076e-10'; $VAR4 = '3.52655463180765e-11'; $VAR5 = '1.03243689459093e-11'; $VAR6 = '0.0328990257518473'; $VAR7 = '7.69239818214629e-09'; $VAR8 = '5.79474017149977e-06'; $VAR9 = '0.000110408896288299'; $VAR10 = '0.00152010910160372'; $VAR11 = '0.00295896662454905'; $VAR12 = '0.0770495813795604'; $VAR13 = '1.34951980004192e-07'; $VAR14 = '3.10075288392397e-05'; $VAR15 = '1.83077391424336e-05'; $VAR16 = '3.5278625619074e-06'; $VAR17 = '0.00502979540436628'; $VAR18 = '0.0105606581968293'; $VAR19 = '0.0216500895829109'; $VAR20 = '0.0240658942029975'; $VAR21 = '0.0497170757799887'; $VAR22 = '0.00111041333816434'; $VAR23 = '0.00169577574481312'; $VAR24 = '0.000736543130562099'; $VAR25 = '0.128732311266979'; $VAR26 = '0.0451561487241565'; $VAR27 = '0.0594906048230024'; $VAR28 = '0.0514732713263945'; $VAR29 = '0.016766199625106'; $VAR30 = '0.068291770630679';
testsize: 2369


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.288279233285587'; $VAR2 = '0.191525907208819'; $VAR3 = '0.295762945370761'; $VAR4 = '0.224431914134832';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.406770956130419'; $VAR3 = 25; $VAR4 = '0.593229043869581';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.074 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.074 Test, Z-Score-Based Method
0.652912621359223
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
0.604992657856094

Author Z-Score-Based P-Values
$VAR1 = '0.0721998066112824'; $VAR2 = '0.0479678445926355'; $VAR3 = '0.0740741093806004'; $VAR4 = '0.0562091851475205';
Decent compatibility. Z-Score-Based P-Value > 0.05.
Decent indicator. 15.1% of the rest have P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '7.46290616031123e-08'; $VAR2 = '0.00522342637784089'; $VAR3 = '5.38436288446265e-08'; $VAR4 = '1.82761278671564e-16'; $VAR5 = '1.50129296816306e-10'; $VAR6 = '0.0346242946459476'; $VAR7 = '9.45431142509033e-09'; $VAR8 = '2.60982470512412e-08'; $VAR9 = '9.72804371207581e-06'; $VAR10 = '0.000194245727973998'; $VAR11 = '0.000769966135367657'; $VAR12 = '0.0234703072882932'; $VAR13 = '3.13501395215851e-09'; $VAR14 = '1.54113147764587e-06'; $VAR15 = '5.22415423228905e-06'; $VAR16 = '1.51379664623893e-08'; $VAR17 = '0.00219567790939371'; $VAR18 = '0.00647235704464878'; $VAR19 = '0.0190381394910012'; $VAR20 = '0.0116851739587222'; $VAR21 = '0.0204011104906904'; $VAR22 = '0.000646333972760104'; $VAR23 = '0.000425134864124438'; $VAR24 = '0.000871218917714633'; $VAR25 = '0.108028639756805'; $VAR26 = '0.0534676361079909'; $VAR27 = '0.0930948386551549'; $VAR28 = '0.0312507056435987'; $VAR29 = '0.0124485536733938'; $VAR30 = '0.0434349513991387';
testsize: 2298


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.281906253085216'; $VAR2 = '0.257122202317103'; $VAR3 = '0.256000227126608'; $VAR4 = '0.204971317471073';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.498111822299399'; $VAR3 = 25; $VAR4 = '0.501888177700601';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.11 Test, Z-Score-Based Method
0.983870967741935
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.11 Test, Z-Score-Based Method
0.146282973621103
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
0.870563674321503

Author Z-Score-Based P-Values
$VAR1 = '0.116320661339688'; $VAR2 = '0.106094222073185'; $VAR3 = '0.105631270667401'; $VAR4 = '0.084575630880721';
Good compatibility. Z-Score-Based P-Value > 0.1.
Decent indicator. 12.1% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '0.000149368599841077'; $VAR2 = '0.000540502674009011'; $VAR3 = '1.32623758416035e-05'; $VAR4 = '2.92979048305352e-09'; $VAR5 = '3.78710044592727e-11'; $VAR6 = '0.0785538803396926'; $VAR7 = '6.96873707314276e-08'; $VAR8 = '0.000352529819829933'; $VAR9 = '0.00119640551526948'; $VAR10 = '0.00559791683820868'; $VAR11 = '0.0115219440269612'; $VAR12 = '0.0794988566480618'; $VAR13 = '1.23048330981284e-05'; $VAR14 = '0.000381503699466092'; $VAR15 = '7.6662688113124e-05'; $VAR16 = '8.19096447523347e-05'; $VAR17 = '0.0124664876106471'; $VAR18 = '0.0271920482271907'; $VAR19 = '0.0424299332437411'; $VAR20 = '0.0195856258028352'; $VAR21 = '0.0662979828086124'; $VAR22 = '0.00309790824746254'; $VAR23 = '0.00743964766829463'; $VAR24 = '0.00683150446281723'; $VAR25 = '0.117202527896667'; $VAR26 = '0.0795287089174086'; $VAR27 = '0.0901575933325815'; $VAR28 = '0.116796923285989'; $VAR29 = '0.0466402375587478'; $VAR30 = '0.056711257839593';
testsize: 2306


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.303771625061145'; $VAR2 = '0.261242299353767'; $VAR3 = '0.280818058188647'; $VAR4 = '0.154168017396441';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.404823493881122'; $VAR3 = 25; $VAR4 = '0.595176506118878';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0856 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0856 Test, Z-Score-Based Method
0.27710843373494
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
0.783018867924528

Author Z-Score-Based P-Values
$VAR1 = '0.0856241894761005'; $VAR2 = '0.0736364370257974'; $VAR3 = '0.0791542614219333'; $VAR4 = '0.0434553804360449';
Decent compatibility. Z-Score-Based P-Value > 0.05.
Decent indicator. 18.1% of the rest have P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '7.74083178597954e-07'; $VAR2 = '0.000270949012040074'; $VAR3 = '9.82914096708235e-07'; $VAR4 = '7.56447810706726e-14'; $VAR5 = '1.8516623194064e-11'; $VAR6 = '0.0182019097467025'; $VAR7 = '1.4409272540559e-10'; $VAR8 = '9.73895642076381e-06'; $VAR9 = '0.000159801385310725'; $VAR10 = '0.00105276645318891'; $VAR11 = '0.00135838257972795'; $VAR12 = '0.0303436350645437'; $VAR13 = '4.14354099891417e-07'; $VAR14 = '2.80119524252887e-05'; $VAR15 = '0.000123147422664379'; $VAR16 = '1.06125575402723e-06'; $VAR17 = '0.00944407105988493'; $VAR18 = '0.00787091949886127'; $VAR19 = '0.0236589082191183'; $VAR20 = '0.00908003436997754'; $VAR21 = '0.0362553242933005'; $VAR22 = '0.00526004996461989'; $VAR23 = '0.000739060236552059'; $VAR24 = '0.000321640170931639'; $VAR25 = '0.125885742062716'; $VAR26 = '0.0523922487121707'; $VAR27 = '0.0606715185915248'; $VAR28 = '0.0372167070044691'; $VAR29 = '0.0377239512212709'; $VAR30 = '0.0535735048376893';
testsize: 2368


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.237197434229784'; $VAR2 = '0.174088144030312'; $VAR3 = '0.296130109256326'; $VAR4 = '0.292584312483578';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.393272303261967'; $VAR3 = 25; $VAR4 = '0.606727696738033';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0962 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0962 Test, Z-Score-Based Method
0.468446601941748
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
0.68099173553719

Author Z-Score-Based P-Values
$VAR1 = '0.0770741722993945'; $VAR2 = '0.0565676422759099'; $VAR3 = '0.0962235664056551'; $VAR4 = '0.0950714065929284';
Decent compatibility. Z-Score-Based P-Value > 0.05.
Poor indicator. 24.2% of the rest have P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '4.38264863809901e-07'; $VAR2 = '0.0011178354530214'; $VAR3 = '7.98854414531393e-09'; $VAR4 = '2.09267961829794e-09'; $VAR5 = '2.14795271260454e-09'; $VAR6 = '0.0358892727195613'; $VAR7 = '1.6015396663598e-08'; $VAR8 = '1.44717986026998e-06'; $VAR9 = '0.000124031286987459'; $VAR10 = '0.00290661672162679'; $VAR11 = '0.00347873959499152'; $VAR12 = '0.0255786384259389'; $VAR13 = '6.76065371934073e-08'; $VAR14 = '6.92773638581917e-06'; $VAR15 = '9.70090972019132e-07'; $VAR16 = '5.40722521966195e-08'; $VAR17 = '0.00090055222747036'; $VAR18 = '0.00713292099152363'; $VAR19 = '0.0107568458259685'; $VAR20 = '0.0195316475279288'; $VAR21 = '0.00904921845105529'; $VAR22 = '3.05635681035895e-05'; $VAR23 = '0.003438752320277'; $VAR24 = '0.00136700154436831'; $VAR25 = '0.148450583305718'; $VAR26 = '0.0577345605007677'; $VAR27 = '0.0924126577447261'; $VAR28 = '0.0692617315259115'; $VAR29 = '0.0130158054198825'; $VAR30 = '0.0756841056658046';
testsize: 2324


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.250784919328855'; $VAR2 = '0.209811855089103'; $VAR3 = '0.301398458781151'; $VAR4 = '0.238004766800891';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 3; $VAR2 = '0.445433999137058'; $VAR3 = 25; $VAR4 = '0.554566000862942';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.11 Test, Z-Score-Based Method
0.982142857142857
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.11 Test, Z-Score-Based Method
0.317422434367542
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
0.755747220673597

Author Z-Score-Based P-Values
$VAR1 = '0.0916704670070725'; $VAR2 = '0.0766934103976851'; $VAR3 = '0.110171447093473'; $VAR4 = '0.0869988840674148';
Good compatibility. Z-Score-Based P-Value > 0.1.
Good indicator. 6% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '2.30785249503336e-07'; $VAR2 = '0.00120116113742904'; $VAR3 = '1.26294191012e-06'; $VAR4 = '2.41121118570071e-09'; $VAR5 = '3.47045791523671e-12'; $VAR6 = '0.0472518317118698'; $VAR7 = '2.89119175825441e-08'; $VAR8 = '3.50623743333201e-05'; $VAR9 = '0.000649408837949475'; $VAR10 = '0.00748382700183306'; $VAR11 = '0.0029872697647937'; $VAR12 = '0.0435131309474289'; $VAR13 = '3.4880722221077e-06'; $VAR14 = '3.92973445167381e-05'; $VAR15 = '6.01917551835567e-05'; $VAR16 = '1.97741224964477e-06'; $VAR17 = '0.00930049377784673'; $VAR18 = '0.00776482444904265'; $VAR19 = '0.0211020337292096'; $VAR20 = '0.0141813254430198'; $VAR21 = '0.0355993748226934'; $VAR22 = '0.00180519691581282'; $VAR23 = '0.00294414770751081'; $VAR24 = '0.00386186607839591'; $VAR25 = '0.137163617825031'; $VAR26 = '0.0444064468425464'; $VAR27 = '0.118817590751023'; $VAR28 = '0.0743832367716028'; $VAR29 = '0.0210125468182929'; $VAR30 = '0.0582460640638309';
testsize: 2329


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.278619641486214'; $VAR2 = '0.237402521514135'; $VAR3 = '0.267934944911691'; $VAR4 = '0.21604289208796';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.448067241438694'; $VAR3 = 25; $VAR4 = '0.551932758561306';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.0991 Test, Z-Score-Based Method
0.983870967741935
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.0991 Test, Z-Score-Based Method
0.196601941747573
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
0.833454931352391

Author Z-Score-Based P-Values
$VAR1 = '0.0991282882111428'; $VAR2 = '0.0844639144935145'; $VAR3 = '0.095326848815707'; $VAR4 = '0.076864509474734';
Decent compatibility. Z-Score-Based P-Value > 0.05.
Poor indicator. 21.2% of the rest have P-Value > 0.05.

Control Z-Score-Based P-Values
$VAR1 = '3.44032050848568e-07'; $VAR2 = '0.00252835990854434'; $VAR3 = '2.25342444060903e-06'; $VAR4 = '3.66166307050866e-13'; $VAR5 = '4.35491136576937e-10'; $VAR6 = '0.0328507342970542'; $VAR7 = '9.90322826496095e-09'; $VAR8 = '1.74203539899644e-07'; $VAR9 = '6.80268575648022e-05'; $VAR10 = '0.00258594549629272'; $VAR11 = '0.00266186271073849'; $VAR12 = '0.0390260751272008'; $VAR13 = '9.4496634111775e-08'; $VAR14 = '3.59229363934771e-05'; $VAR15 = '1.0801107017772e-05'; $VAR16 = '9.17983267525138e-07'; $VAR17 = '0.00424811069366068'; $VAR18 = '0.0138227030089183'; $VAR19 = '0.0306531847543016'; $VAR20 = '0.0262886472415909'; $VAR21 = '0.0406283516536747'; $VAR22 = '0.000672481805758074'; $VAR23 = '0.00139369728590873'; $VAR24 = '0.00193095427136824'; $VAR25 = '0.122107006502331'; $VAR26 = '0.0515288796613301'; $VAR27 = '0.0794492853736719'; $VAR28 = '0.0385017676908508'; $VAR29 = '0.00854384464317116'; $VAR30 = '0.0541037488361445';
testsize: 2312


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.201071392563844'; $VAR2 = '0.184414905793091'; $VAR3 = '0.298741938519104'; $VAR4 = '0.315771763123962';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 4; $VAR2 = '0.475331347767996'; $VAR3 = 25; $VAR4 = '0.524668652232005';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.15 Test, Z-Score-Based Method
0.903225806451613
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.15 Test, Z-Score-Based Method
0.0674157303370786
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
0.930545182972367

Author Z-Score-Based P-Values
$VAR1 = '0.0975109936130183'; $VAR2 = '0.0894333125744167'; $VAR3 = '0.144877015508945'; $VAR4 = '0.153135749370092';
Good compatibility. Z-Score-Based P-Value > 0.15.
Great indicator. 3% of the rest have P-Value > 0.15.

Control Z-Score-Based P-Values
$VAR1 = '8.388923386072e-05'; $VAR2 = '0.00356321806859909'; $VAR3 = '0.00049690637413872'; $VAR4 = '1.33013217547012e-06'; $VAR5 = '5.53807809974062e-10'; $VAR6 = '0.0658930913209952'; $VAR7 = '3.17869376797095e-07'; $VAR8 = '0.000116689400071278'; $VAR9 = '0.000529918431838463'; $VAR10 = '0.00548964285505543'; $VAR11 = '0.0089064036976262'; $VAR12 = '0.0642370401173056'; $VAR13 = '2.84736281302131e-07'; $VAR14 = '9.76452977311847e-05'; $VAR15 = '7.91148654141185e-06'; $VAR16 = '5.08447828727935e-06'; $VAR17 = '0.00329162523176086'; $VAR18 = '0.013150962072615'; $VAR19 = '0.0124185160973647'; $VAR20 = '0.0219568502092728'; $VAR21 = '0.0369047008242823'; $VAR22 = '0.000478969644776746'; $VAR23 = '0.00181426569809894'; $VAR24 = '0.00247820388021937'; $VAR25 = '0.169030567009353'; $VAR26 = '0.067991102075992'; $VAR27 = '0.108320688412532'; $VAR28 = '0.0889182783812247'; $VAR29 = '0.0258794943564531'; $VAR30 = '0.0797199397489088';
testsize: 2388


Bayesian Author Test: Posterior Probabilities from Equal Priors, Z-Score-Based Method
$VAR1 = '0.345760708660716'; $VAR2 = '0.283169604924781'; $VAR3 = '0.151569493737316'; $VAR4 = '0.219500192677187';

Bayesian Comparison of Best Author to Best Control: from Equal Priors, Z-Score-Based Method
$VAR1 = 1; $VAR2 = '0.516123204490954'; $VAR3 = 25; $VAR4 = '0.483876795509046';

Percentage of Samples in the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
1
Percentage of Samples outside the Best Author Candidate that Meet the P-Value>0.13 Test, Z-Score-Based Method
0.0975
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
0.911161731207289

Author Z-Score-Based P-Values
$VAR1 = '0.130718074635097'; $VAR2 = '0.107054921579509'; $VAR3 = '0.0573022668524201'; $VAR4 = '0.0829841038906182';
Good compatibility. Z-Score-Based P-Value > 0.1.
Good indicator. 6% of the rest have P-Value > 0.1.

Control Z-Score-Based P-Values
$VAR1 = '1.11298811945325e-05'; $VAR2 = '0.00286510967289016'; $VAR3 = '5.95302893745893e-08'; $VAR4 = '1.84065517217085e-13'; $VAR5 = '1.24557744814511e-09'; $VAR6 = '0.0155674961267867'; $VAR7 = '4.04056157294609e-08'; $VAR8 = '8.76101360190774e-09'; $VAR9 = '6.61530344252627e-05'; $VAR10 = '0.000252704168025867'; $VAR11 = '0.00718218030451941'; $VAR12 = '0.0220561204241966'; $VAR13 = '9.7446169848885e-08'; $VAR14 = '0.000110738240014313'; $VAR15 = '6.75532989389081e-05'; $VAR16 = '5.14893631246808e-06'; $VAR17 = '0.0105911364218112'; $VAR18 = '0.0143051538064505'; $VAR19 = '0.0190163285103943'; $VAR20 = '0.0190390293667262'; $VAR21 = '0.017326668525287'; $VAR22 = '0.000718929170690619'; $VAR23 = '0.00216375200914482'; $VAR24 = '0.000884599429652453'; $VAR25 = '0.122551054707813'; $VAR26 = '0.0665809970943128'; $VAR27 = '0.0332631733808582'; $VAR28 = '0.0268808585557976'; $VAR29 = '0.00882115955943976'; $VAR30 = '0.068056289616831';
"... almost every critical biblical position was earlier advanced by skeptics." - Raymond Brown

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Secret Alias
Posts: 11232
Joined: Sun Apr 19, 2015 8:47 am

Re: Origen -- A Basic Stylometric Study

Post by Secret Alias » Sat Jun 06, 2015 5:47 pm

The text may have been written by Clement of Alexandria, by Origen or both
“Finally, from so little sleeping and so much reading, his brain dried up and he went completely out of his mind.”
― Miguel de Cervantes Saavedra, Don Quixote

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