Package: tcftt 0.1.0
tcftt: Two-Sample Tests for Skewed Data
The classical two-sample t-test works well for the normally distributed data or data with large sample size. The tcfu() and tt() tests implemented in this package provide better type-I-error control with more accurate power when testing the equality of two-sample means for skewed populations having unequal variances. These tests are especially useful when the sample sizes are moderate. The tcfu() uses the Cornish-Fisher expansion to achieve a better approximation to the true percentiles. The tt() provides transformations of the Welch's t-statistic so that the sampling distribution become more symmetric. For more technical details, please refer to Zhang (2019) <http://hdl.handle.net/2097/40235>.
Authors:
tcftt_0.1.0.tar.gz
tcftt_0.1.0.zip(r-4.5)tcftt_0.1.0.zip(r-4.4)tcftt_0.1.0.zip(r-4.3)
tcftt_0.1.0.tgz(r-4.4-any)tcftt_0.1.0.tgz(r-4.3-any)
tcftt_0.1.0.tar.gz(r-4.5-noble)tcftt_0.1.0.tar.gz(r-4.4-noble)
tcftt_0.1.0.tgz(r-4.4-emscripten)tcftt_0.1.0.tgz(r-4.3-emscripten)
tcftt.pdf |tcftt.html✨
tcftt/json (API)
NEWS
| # Install 'tcftt' in R: |
| install.packages('tcftt', repos = c('https://huaiyuzhang.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/huaiyuzhang/tcftt/issues
Last updated 1 years agofrom:e12bfd9ed3. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Oct 31 2024 |
| R-4.5-win | OK | Oct 31 2024 |
| R-4.5-linux | OK | Oct 31 2024 |
| R-4.4-win | OK | Oct 31 2024 |
| R-4.4-mac | OK | Oct 31 2024 |
| R-4.3-win | OK | Oct 31 2024 |
| R-4.3-mac | OK | Oct 31 2024 |
Exports:adjust_powerboot_testpauct_cornish_fishert_edgeworthtcfutt
Dependencies:
