In AmandaRP/hddtest: Hypothesis Testing for High Dimensional Discrete Data

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hddtest

Functions for two sample hypothesis testing of high dimensional discrete data, specifically multinomial and multivariate binary data.

Installation

You can install hddtest from github with:

install.packages("devtools")
devtools::install_github("AmandaRP/hddtest", build_vignettes = TRUE)
library("hddtest")

Example

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()

Available functions and datasets

See help documentation on each of the following via ?functionname

• multinom.test
• multinom.neighborhood.test
• genMultinomialData
• mvbinary.test
• genMVBinaryData
• twoNewsGroups

Vignette

Read more about the multinomial neighborhood test:

vignette("multinomial-neighborhood-test-vignette")

References

[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

AmandaRP/hddtest documentation built on March 18, 2023, 5:53 p.m.