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.
- Version0.1.0
- R version≥ 3.1.0
- LicenseGPL-2
- Needs compilation?No
- Last release07/23/2020
Documentation
Team
Huaiyu Zhang
Haiyan Wang
Show author detailsRolesAuthor
Insights
Last 30 days
Last 365 days
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN