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Bartlett correction of an independence test in a multivariate Poisson model

Published 18 Mar 2021 in math.ST, stat.ME, and stat.TH | (2103.10058v1)

Abstract: We consider a system of dependent Poisson variables, where each variable is the sum of an independent variate and a common variate. It is the common variate that creates the dependence. Within this system, a test of independence may be constructed where the null hypothesis is that the common variate is identically zero. In the present paper, we consider the maximum log likelihood ratio test. For this test, it is well-known that the asymptotic distribution of the test statistic is an equal mixture of zero and a chi square distribution with one degree of freedom. We examine a Bartlett correction of this test, in the hope that we will get better approximation of the nominal size for moderately large sample sizes. This correction is explicitly derived, and its usefulness is explored in a simulation study. For practical purposes, the correction is found to be useful in dimension two, but not in higher dimensions.

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