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Choosing the best Rukhin goodness-of-fit statistics

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Marhuenda García, Yolanda and Morales González, Domingo and Pardo Llorente, Julio Ángel and Pardo Llorente, María del Carmen (2005) Choosing the best Rukhin goodness-of-fit statistics. Computational Statistics and Data Analysis, 49 (3). pp. 643-662. ISSN 0167-9473

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Official URL: http://www.sciencedirect.com/science/article/pii/S0167947304001756


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Abstract

The testing for goodness-of-fit in multinomial sampling contexts is usually based on the asymptotic distribution of Pearson-type chi-squared statistics. However, approximations are not justified for those cases where sample size and number of cells permit the use of adequate algorithms to calculate the exact distribution of test statistics in a reasonable time. In particular, Rukhin statistics, containing chi(2) and Neyman's modified chi(2) statistics, are considered for testing uniformity. Their exact distributions are calculated for different sample sizes and number of cells. Several exact power comparisons are carried out to analyse the behaviour of selected statistics. As a result of the numerical study some recommendations are given. Conclusions may be extended to testing the goodness of fit to a given absolutely continuous cumulative distribution function.


Item Type:Article
Uncontrolled Keywords:Goodness-of-fit statistics; Rukhin’s divergence; Algorithms; Exact distribution function; Exact powers
Subjects:Sciences > Mathematics > Mathematical statistics
ID Code:17494
Deposited On:20 Dec 2012 10:56
Last Modified:25 Jul 2018 10:48

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