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tcftt  

Two-Sample Tests for Skewed Data
View on CRAN: Click here


Download and install tcftt package within the R console
Install from CRAN:
install.packages("tcftt")

Install from Github:
library("remotes")
install_github("cran/tcftt")

Install by package version:
library("remotes")
install_version("tcftt", "0.1.0")



Attach the package and use:
library("tcftt")
Maintained by
Huaiyu Zhang
[Scholar Profile | Author Map]
First Published: 2020-07-23
Latest Update: 2020-07-23
Description:
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>.
How to cite:
Huaiyu Zhang (2020). tcftt: Two-Sample Tests for Skewed Data. R package version 0.1.0, https://cran.r-project.org/web/packages/tcftt. Accessed 06 Apr. 2025.
Previous versions and publish date:
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Complete documentation for tcftt
Functions, R codes and Examples using the tcftt R package
Some associated functions: adjust_power . boot_test . compute_t . pauc . t_cornish_fisher . t_edgeworth . tcftt . tcfu . tt . 
Some associated R codes: functions.R . tcftt.R .  Full tcftt package functions and examples
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