Nonparametric Goodness-of-Fit Tests for Discrete Null Distributions
Taylor B. Arnold and John W. Emerson
, The R Journal (2011) 3:2, pages 34-39.
Abstract 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.
@article{RJ-2011-016, author = {Taylor B. Arnold and John W. Emerson}, title = {{Nonparametric Goodness-of-Fit Tests for Discrete Null Distributions}}, year = {2011}, journal = {{The R Journal}}, doi = {10.32614/RJ-2011-016}, url = {https://doi.org/10.32614/RJ-2011-016}, pages = {34--39}, volume = {3}, number = {2} }