Methodology extending nonparametric goodness-of-fit tests to discrete null distributions has existed for several decades. However, modern statistical software has generally failed to provide this methodology to users. We offer a revision of R’s ks.test() function and a new cvm.test() function that fill this need in the R language for two of the most popular nonparametric goodness-of-fit tests. This paper describes these contributions and provides examples of their usage. Particular attention is given to various numerical issues that arise in their implementation.
dgof, nortest, ADGofTest, CvM2SL1Test, CvM2SL2Test, cramer
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For attribution, please cite this work as
Arnold & Emerson, "The R Journal: Nonparametric Goodness-of-Fit Tests for Discrete Null Distributions", The R Journal, 2011
BibTeX citation
@article{RJ-2011-016,
author = {Arnold, Taylor B. and Emerson, John W.},
title = {The R Journal: Nonparametric Goodness-of-Fit Tests for Discrete Null Distributions},
journal = {The R Journal},
year = {2011},
note = {https://doi.org/10.32614/RJ-2011-016},
doi = {10.32614/RJ-2011-016},
volume = {3},
issue = {2},
issn = {2073-4859},
pages = {34-39}
}