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:Huaiyu Zhang, Haiyan Wang

tcftt_0.1.0.tar.gz
tcftt_0.1.0.zip(r-4.7)tcftt_0.1.0.zip(r-4.6)tcftt_0.1.0.zip(r-4.5)
tcftt_0.1.0.tgz(r-4.6-any)tcftt_0.1.0.tgz(r-4.5-any)
tcftt_0.1.0.tar.gz(r-4.7-any)tcftt_0.1.0.tar.gz(r-4.6-any)
tcftt_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html
card.svg |card.png
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

On CRAN:

Conda:

2.70 score 1 stars 1 scripts 153 downloads 7 exports 0 dependencies

Last updated from:e12bfd9ed3. Checks:9 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-x86_64OK125
source / vignettesOK129
linux-release-x86_64OK92
macos-release-arm64OK92
macos-oldrel-arm64OK74
windows-develOK65
windows-releaseOK79
windows-oldrelOK52
wasm-releaseOK80

Exports:adjust_powerboot_testpauct_cornish_fishert_edgeworthtcfutt

Dependencies: