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>.
| Version: |
0.1.0 |
| Depends: |
R (≥ 3.1.0) |
| Imports: |
stats |
| Published: |
2020-07-23 |
| DOI: |
10.32614/CRAN.package.tcftt |
| Author: |
Huaiyu Zhang, Haiyan Wang |
| Maintainer: |
Huaiyu Zhang <huaiyuzhang1988 at gmail.com> |
| License: |
GPL-2 |
| NeedsCompilation: |
no |
| Materials: |
README NEWS |
| CRAN checks: |
tcftt results |
Documentation:
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