robnptests -- An R package for robust two-sample location and dispersion tests

robnptests -- An R package for robust two-sample location and dispersion tests - Published in JOSS (2023)

https://github.com/s-abbas/robnptests

Science Score: 95.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
    Found codemeta.json file
  • .zenodo.json file
    Found .zenodo.json file
  • DOI references
    Found 1 DOI reference(s) in JOSS metadata
  • Academic publication links
  • Committers with academic emails
    3 of 7 committers (42.9%) from academic institutions
  • Institutional organization owner
  • JOSS paper metadata
    Published in Journal of Open Source Software
Last synced: 6 months ago · JSON representation

Repository

Robust two-sample tests for the location problem

Basic Info
  • Host: GitHub
  • Owner: s-abbas
  • License: gpl-2.0
  • Language: R
  • Default Branch: main
  • Size: 1.32 MB
Statistics
  • Stars: 2
  • Watchers: 2
  • Forks: 2
  • Open Issues: 0
  • Releases: 1
Created about 7 years ago · Last pushed about 3 years ago
Metadata Files
Readme Changelog Contributing License

README.md

robnptests

Codecov test coverage <!-- badges: end -->

The R package robnptests contains different robust and nonparametric tests for the two-sample location problem. The tests allow for comparisons of either the location or the scale parameters of two random samples.

Installation

The released version of robnptests can be installed from CRAN with

{r} install.packages("robnptests")

To install the development version, the devtools package is required:

``` r if (!require("devtools")) { install.packages("devtools") }

devtools::install_github("s-abbas/robnptests")

library(robnptests) ```

Scope and Usage

The robust and nonparametric tests in this R package follow the construction principle of the popular t-test: A robust estimate for the location difference of the two samples is divided by a robust estimate of scale. The p-values can either be computed using the permutation principle, the randomization principle, or the asymptotic distribution of the estimators. If the principle to compute the p-value is not specified by the user, it will be selected automatically depending on the sample size. The functions used to compute the location and scale estimates are also made available to the user.

The following list shows the currently implemented tests in the package:

  • tests based on the median (med_test), the one-sample Hodges-Lehmann estimator (hl1_test), and the two-sample Hodges-Lehmann estimator (hl2_test), scaled by robust estimators
  • Yuen's t-test (trimmed_test)
  • tests based on the Huber-, Hampel- or Bisquare-M-estimator (m_test).

Even though the test statistics compare location estimates of the samples, they can be used to identify scale differences. This is achieved by setting the argument scale.test = TRUE, with which the observations in the samples are log-transformed so that scale differences between the original samples correspond to location differences in the transformed samples.

Details on the tests and references can be found on the help pages of the functions and the vignette vignette("robnptests").

Example 1: Asymptotic test for location difference using the two-sample Hodges-Lehmann estimator

``` r set.seed(121) x <- rnorm(50); y <- rnorm(50)

hl2_test(x, y, method = "asymptotic")

Asymptotic test based on HL2-estimator

data: x and y

D = 1.0916, p-value = 0.275

alternative hypothesis: true location shift is not equal to 0

sample estimates:

HL2 of x and y

0.2048249

```

Example 2: Asymptotic test for scale difference using the two-sample Hodges-Lehmann estimator

``` r hl2_test(x, y, method = "asymptotic", scale.test = TRUE)

Asymptotic test based on HL2-estimator

data: x and y

S = -0.24094, p-value = 0.8096

alternative hypothesis: true ratio of variances is not equal to 1

sample estimates:

HL2 of log(x^2) and log(y^2)

-0.1040422

```

Contributions

We are grateful for any contribution to the further development of the R package. If you experience any problems using the package or have suggestions for new features, please open an issue in the issue tracker. Please consult our contribution guidelines before submitting a pull request.

JOSS Publication

robnptests -- An R package for robust two-sample location and dispersion tests
Published
February 15, 2023
Volume 8, Issue 82, Page 4947
Authors
Sermad Abbas ORCID
TU Dortmund University, Faculty of Statistics, 44221 Dortmund, Germany
Barbara Brune ORCID
Technical University of Vienna, Institute of Statistics and Mathematical Methods in Economics, 1040 Vienna, Austria
Roland Fried ORCID
TU Dortmund University, Faculty of Statistics, 44221 Dortmund, Germany
Editor
Mehmet Hakan Satman ORCID
Tags
robust statistics nonparametric statistics

GitHub Events

Total
Last Year

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 392
  • Total Committers: 7
  • Avg Commits per committer: 56.0
  • Development Distribution Score (DDS): 0.26
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
s-abbas s****s@t****e 290
b-brune b****e@s****e 44
b-brune b****e@t****e 34
Barbara Brune b****e@t****t 13
b-brune b****e@a****t 6
= = 4
Mehmet Hakan Satman m****n@g****m 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 1
  • Total pull requests: 8
  • Average time to close issues: 28 days
  • Average time to close pull requests: about 17 hours
  • Total issue authors: 1
  • Total pull request authors: 2
  • Average comments per issue: 2.0
  • Average comments per pull request: 0.13
  • Merged pull requests: 8
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • mingzehuang (1)
Pull Request Authors
  • s-abbas (7)
  • jbytecode (1)
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • cran 227 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 0
  • Total versions: 2
  • Total maintainers: 1
cran.r-project.org: robnptests

Robust Nonparametric Two-Sample Tests for Location/Scale

  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 227 Last month
Rankings
Forks count: 17.8%
Stargazers count: 28.5%
Dependent packages count: 29.8%
Average: 33.8%
Dependent repos count: 35.5%
Downloads: 57.3%
Last synced: 6 months ago

Dependencies

DESCRIPTION cran
  • R >= 4.0.0 depends
  • Rdpack * imports
  • checkmate * imports
  • gtools * imports
  • robustbase * imports
  • statmod * imports
  • stats * imports
  • utils * imports
  • covr * suggests
  • knitr * suggests
  • rmarkdown * suggests
  • testthat * suggests
  • usethis * suggests
.github/workflows/draft-pdf.yml actions
  • actions/checkout v2 composite
  • actions/upload-artifact v1 composite
  • openjournals/openjournals-draft-action master composite