Simulation Studies For Goodness-of-Fit and Two-Sample Methods For Univariate Data
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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.
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Goodness of Fit Tests Based on Joint Densities of Multiple Sample Statistics
Goodness-of-fit tests are developed using simulated hyperrectangular and highest-density-region confidence sets for joint distributions of multiple sample statistics, with simulations indicating competitive or superio...
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