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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.0 |
rolling linux/jammy R-4.5 | tcftt_0.1.0.tar.gz |
46.5 KiB |
0.1.0 |
rolling linux/noble R-4.5 | tcftt_0.1.0.tar.gz |
46.4 KiB |
0.1.0 |
rolling source/ R- | tcftt_0.1.0.tar.gz |
8.4 KiB |
0.1.0 |
latest linux/jammy R-4.5 | tcftt_0.1.0.tar.gz |
46.5 KiB |
0.1.0 |
latest linux/noble R-4.5 | tcftt_0.1.0.tar.gz |
46.4 KiB |
0.1.0 |
latest source/ R- | tcftt_0.1.0.tar.gz |
8.4 KiB |
0.1.0 |
2026-04-26 source/ R- | tcftt_0.1.0.tar.gz |
8.4 KiB |
0.1.0 |
2026-04-23 source/ R- | tcftt_0.1.0.tar.gz |
8.4 KiB |
0.1.0 |
2026-04-09 windows/windows R-4.5 | tcftt_0.1.0.zip |
49.2 KiB |
0.1.0 |
2025-04-20 source/ R- | tcftt_0.1.0.tar.gz |
8.4 KiB |