README.md

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

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]])
#> $statistic
#> [1] 13.63883
#> 
#> $pvalue
#> [1] 0

The last call can also be done using a pipe:

data |> multinom.test()
#> $statistic
#> [1] 13.63883
#> 
#> $pvalue
#> [1] 0

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.