A two sample test based on mutual information
Abstract
For two independently drawn samples from continuous
distributions, a permutation test based on the mutual information statistic is proposed for the null hypothesis that both the samples originate
from the same population. It is demonstrated through simulation that
this test is more powerful than the commonly used nonparametric tests
in many situations. We also discuss the test in a real-life setup.
Keywords and phrases: Nonparametric Test; Two-Sample Test; Information Theory; Permutation Test; Kernel Density Estimation.
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