CODEWITHSUNDEEP
pythonscipy
burcak
burcak

Reputation: 1147

Scipy fisher_exact test taking a very long time

I'm using scipy version 1.0.0.

import scipy as sp
x = [[5829225, 5692693], [5760959, 5760959]]
sp.stats.fisher_exact(x)

For the values above scipy does not return anything but waits. What can be the reason for that? How can I fix it?

However in R it returns a p-value almost immediately.

a = matrix(c(5829225,5692693,5760959,5760959), nrow=2)
fisher.test(a)

Upvotes: 4

Views: 1479

Answers (1)

TayTay
TayTay

Reputation: 7160

From the notes in the documentation:

The calculated odds ratio is different from the one R uses. This scipy implementation returns the (more common) “unconditional Maximum Likelihood Estimate”, while R uses the “conditional Maximum Likelihood Estimate”.

For tables with large numbers, the (inexact) chi-square test implemented in the function chi2_contingency can also be used.

(Emphasis mine)

Like DSM's comment mentioned, it's probably just very slow for your large values. And since the notes call out large values, you might try the alternative they suggest:

>>> chi2, p, dof, expected = sp.stats.chi2_contingency(x)
>>> p
6.140729432506709e-178

Upvotes: 3

Related Questions