Package: tcftt 0.1.0

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>.

Authors:Huaiyu Zhang, Haiyan Wang

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Bug tracker:https://github.com/huaiyuzhang/tcftt/issues

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Exports:adjust_powerboot_testpauct_cornish_fishert_edgeworthtcfutt

Dependencies: