multiple-hypothesis-testing 0.1.2

Several methods of combining P-values

MultiTest -- Global Tests for Multiple Hypothesis

MultiTest includes several techniques for multiple hypothesis testing:

• MultiTest.hc Higher Criticism
• MultiTest.hcstar Higher Criticism with limited range
• MultiTest.hc_jin Higher Criticism with limited range proposed by Jiashun Jin
• MultiTest.berk_jones Berk-Jones test (actually -log(bj))
• MultiTest.fdr False-discovery rate with optimized rate parameter
• MultiTest.minp Minimal P-values (Bonferroni style inference) (actually -log(minp))
• MultiTest.fisher Fisher's method to combine P-values

All tests rejects for large values of the test statistics.

Example:

import numpy as np
from scipy.stats import norm
from multitest import MultiTest

p = 10
z = np.random.randn(p)
pvals = 2*norm.cdf(-np.abs(z)/2)

mtest = MultiTest(pvals)

f = mtest.fisher()
bj = mtest.berk_jones()

print(f"Fisher = {f[0]}, degrees of freedom = {f[1]}")
print(f"Berk-Jones = {bj}")