Improving Accuracy of Goodness-of-fit Test
Statistics Theory
2014-10-28 v1 Statistics Theory
Abstract
It is well known that the approximate distribution of the usual test statistic of a goodness-of-fit test is chi-square, with degrees of freedom equal to the number of categories minus 1 (assuming that no parameters are to be estimated -- something we do throughout this article). Here we show how to improve this approximation by including two correction terms, each of them inversely proportional to the total number of observations.
Keywords
Cite
@article{arxiv.1410.6869,
title = {Improving Accuracy of Goodness-of-fit Test},
author = {Kris Duszak and Jan Vrbik},
journal= {arXiv preprint arXiv:1410.6869},
year = {2014}
}