README.md

In sidoruvigo/TwoSampleTest.HD: A Two-Sample Test for the Equality of Distributions for High-Dimensional Data

TwoSampleTest.HD

SiDOR Group. University of Vigo.

Install the development version from GitHub

devtools::install_github('sidoruvigo/TwoSampleTest.HD')

This package implements four different tests proposed in Cousido-Rocha et al. (2018). These methods test the (global) null hypotheses of equality of the univariate marginals of the p-variate distributions in the two populations. In other words, the null hypotheses is an intersection of the p null hypotheses corresponding to p different two-sample problems. These methods are particularly well suited to the low sample size, high dimensional setting (n << p). The sample size can be as small as 2. The test accounts for the possibility that the p variables in each data set can be weakly dependent. Three of the methods arise from different approaches to estimate the variance of the same statistic. This statistic averages p individual statistics based on comparing the empirical characteristic functions computed from the two samples. The last method is an alternative global test whose statistic averages the p-values derived from applying permutation tests to the individual statistics mentioned above. When the global null hypotheses is rejected such permutation p-values can also be used to identify which variables contribute to this significance. The standarized version of each test statistic and its p-value are computed among other things.

Maintainer

Marta Cousido Rocha.

Authors

• Cousido Rocha, Marta.
• Soage González, José Carlos.
• de Uña-Álvarez, Jacobo.
• D. Hart, Jeffrey.

References

Cousido-Rocha, M., de Uña-Álvarez J., and Hart, J. (2018). A two-sample test for the equality of distributions for high-dimensional data. Preprint.

sidoruvigo/TwoSampleTest.HD documentation built on May 27, 2019, 9:56 a.m.