On disparity based goodness-of-fit tests for multinomial models

Ayenendranath Basu and Sahadeb Sarkar

Statistics & Probability Letters, 1994, vol. 19, issue 4, 307-312

Abstract: A general class of goodness-of-fit tests called disparity tests containing the family of power weighted divergence statistics as a subclass is considered. Under the simple and composite null hypotheses the asymptotic distribution of disparity tests is shown to be chi-square. It is also shown that the blended weight Hellinger distance subfamily, like the power weighted divergence subfamily, has a member that gives an excellent compromise between the Pearson's chi-square and the log likelihood ratio tests.

Keywords: Best; asymptotically; normal; estimator; blended; weight; Hellinger; distance; blended; weight; chi-square; goodness-of-fit; Hellinger; distance; likelihood; ratio; test; minimum; disparity; estimation (search for similar items in EconPapers)
Date: 1994
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Citations: View citations in EconPapers (3)

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