Package: RobustBF 0.2.0
Gamze Guven
RobustBF: Robust Solution to the Behrens-Fisher Problem
Robust tests (RW and RF) are provided for testing the equality of two long-tailed symmetric (LTS) means when the variances are unknown and arbitrary. RW test is a robust version of Welch's two sample t test and the RF is a robust fiducial based test. The RW and RF tests are proposed using the adaptive modified maximum likelihood (AMML) estimators derived by Tiku and Surucu (2009) <doi:10.1016/j.spl.2008.12.001> and Donmez (2010) <https://open.metu.edu.tr/bitstream/handle/11511/19440/index.pdf>.
Authors:
RobustBF_0.2.0.tar.gz
RobustBF_0.2.0.tar.gz(r-4.5-noble)RobustBF_0.2.0.tar.gz(r-4.4-noble)
RobustBF_0.2.0.tgz(r-4.4-emscripten)RobustBF_0.2.0.tgz(r-4.3-emscripten)
RobustBF.pdf |RobustBF.html✨
RobustBF/json (API)
| # Install 'RobustBF' in R: |
| install.packages('RobustBF', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:b8e2ea277d. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-linux | OK | Oct 31 2024 |
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Robust Fiducial Based Test | RF |
| Robust Welch's Two Sample t-Test | RW |