HuaiyuZhang/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>.

Getting started

Package details

AuthorHuaiyu Zhang, Haiyan Wang
MaintainerHuaiyu Zhang <huaiyuzhang1988@gmail.com>
LicenseGPL-2
Version0.1.0
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("HuaiyuZhang/tcftt")
HuaiyuZhang/tcftt documentation built on July 21, 2020, 8:55 p.m.