Distribution-Free Exact High Dimensional Low Sample Size k-Sample Tests
Overview
Testing homogeneity of k multivariate distributions is a classical and challenging problem in statistics, and this becomes even more challenging when the dimension of the data exceeds the sample size. We construct some tests for this purpose which are exact level (size) alpha tests based on clustering. These tests are easy to implement and distribution-free in finite sample situations. Under appropriate regularity conditions, these tests have the consistency property in HDLSS asymptotic regime, where the dimension of data grows to infinity while the sample size remains fixed. We also consider a multiscale approach, where the results for different number of partitions are aggregated judiciously. Details are in Biplab Paul, Shyamal K De and Anil K Ghosh (2021) doi:10.1016/j.jmva.2021.104897; Soham Sarkar and Anil K Ghosh (2019) doi:10.1109/TPAMI.2019.2912599; William M Rand (1971) doi:10.1080/01621459.1971.10482356; Cyrus R Mehta and Nitin R Patel (1983) doi:10.2307/2288652; Joseph C Dunn (1973) doi:10.1080/01969727308546046; Sture Holm (1979) doi:10.2307/4615733; Yoav Benjamini and Yosef Hochberg (1995) <doi: 10.2307/2346101>.
Install
Health
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-01
- OK14 OK2026-04-22
- ERROR13 OK, 1 ERROR2026-04-18
- OK14 OK2026-03-10
Documentation
- Help pages
- 14includes a package overview page
- Examples that run
- 100%13 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- not tracked
- Return-value docs
- not tracked
- Help pages citing references
- 100%
Downloads
Dependencies
Installing HDLSSkST adds 1 package (1 with compiled code, 1.8 MB of source tarballs). Heaviest: Rcpp 1.8 MB.
Code & Tests
People & History
Package metadata
- First published
- 2020-08-04
- Total releases
- 4 / 6 yrs
- License
- GPL (>= 2) OSI
- Download size
- 15 KB
Cite
Cite this package
Run in R for the authors' preferred citation:
citation("HDLSSkST")This package has no citation file, so citation() returns this entry built from DESCRIPTION.
Cite the R Observatory
For a number measured here: a download total, a coverage figure, an archival date.
From data release v2026-10-21, which the citation names so these numbers can be found later. More on citing and the projects behind them.