We present the results of a large number of simulation studies regarding the power of various goodness-of-fit as well as nonparametric two-sample tests for univariate data. This includes both continuous and discrete data. In general no single method can be relied upon to provide good power, any one method may be quite good for some combination of null hypothesis and alternative and may fail badly for another. Based on the results of these studies we propose a fairly small number of methods chosen such that for any of the case studies included here at least one of the methods has good power. The studies were carried out using the R packages R2sample and Rgof, available from CRAN.

翻译：本文针对单变量数据（包括连续型和离散型数据）的多种拟合优度检验及非参数双样本检验的功效，开展了大量仿真研究并报告其结果。总体而言，没有任何单一方法能够始终保证良好的检验功效；任一方法可能对某些原假设与备择假设的组合表现优异，而对其他组合则可能严重失效。基于这些研究结果，我们提出一个数量相对较少的方法集合，其选取原则是：对于本文包含的所有案例研究，至少有一种方法能保持较高的检验功效。本研究使用CRAN提供的R软件包R2sample与Rgof完成。