MyFisher

the definitive function for the Fisher's exact and conditional test for any RxC matrix
1,1K Downloads
Aktualisiert 8 Nov 2021

Fisher's Exact Probability Test for a RxC matrix.
Fisher's exact test permits calculation of precise probabilities in situation where, as a consequence of small cell frequencies, the much more rapid normal approximation and chi-square calculations are liable to be inaccurate. The Fisher's exact test involves the computations of several factorials to obtain the probability of the observed and each of the more extreme tables. Factorials growth quickly, so it's necessary use logarithms of factorials. This computations is very easy in Matlab because: x!=gamma(x+1) and log(x!)=gammaln(x+1). Moreover, when the matrix has many Rows and Columns, the computation of all the set of possible matrices is very time expensive. This function uses this strategy:
if the input is a 2x2, 2x3, 2x4 or 3x3 matrix it uses (or download) ad hoc, previously written by me, function;

else it uses a Monte Carlo approach. Finally, this function uses the Peter J. Acklam rldecode function, and so I want to acknowledge him.

Created by Giuseppe Cardillo
giuseppe.cardillo-edta@poste.it

To cite this file, this would be an appropriate format: Cardillo G. (2010) MyFisher: the definitive function for the Fisher's exact and conditional test for any RxC matrix http://www.mathworks.com/matlabcentral/fileexchange/26883

Zitieren als

Giuseppe Cardillo (2024). MyFisher (https://github.com/dnafinder/myfisher), GitHub. Abgerufen .

Kompatibilität der MATLAB-Version
Erstellt mit R2014b
Kompatibel mit allen Versionen
Plattform-Kompatibilität
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Versionen, die den GitHub-Standardzweig verwenden, können nicht heruntergeladen werden

Version Veröffentlicht Versionshinweise
2.0.0.0

inputparser; table implementation; github link

1.1.0.0

change in help section for citation

1.0.0.0

Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.
Um Probleme in diesem GitHub Add-On anzuzeigen oder zu melden, besuchen Sie das GitHub Repository.