knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "README-" ) devtools::load_all()
Functions for two sample hypothesis testing of high dimensional discrete data, specifically multinomial and multivariate binary data.
You can install hddtest from github with:
install.packages("devtools") devtools::install_github("AmandaRP/hddtest", build_vignettes = TRUE) library("hddtest")
Generate two multinomial vectors and test whether they come from the same underlying distribution:
data <- genMultinomialData(null_hyp=FALSE, sample_size = 1) multinom.test(x=data[[1]], y=data[[2]])
The last call can also be done using a pipe:
data |> multinom.test()
See help documentation on each of the following via ?functionname
multinom.test
multinom.neighborhood.test
genMultinomialData
mvbinary.test
genMVBinaryData
twoNewsGroups
Read more about the multinomial neighborhood test:
vignette("multinomial-neighborhood-test-vignette")
[1] Plunkett, A. & Park, J. (2018) Two-sample test for sparse high-dimensional multinomial distributions, TEST, doi.org/10.1007/s11749-018-0600-8
[2] Plunkett, A. & Park, J. (2017) Two-sample tests for sparse high-dimensional binary data, Communications in Statistics - Theory and Methods, 46:22, 11181-11193, DOI: 10.1080/03610926.2016.1260743
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