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arXiv · 2306.17014

Poisson and Gaussian approximations of the power divergence family of statistics

Fraser Daly
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Abstract

Consider the family of power divergence statistics based on $n$ trials, each leading to one of $r$ possible outcomes. This includes the log-likelihood ratio and Pearson's statistic as important special cases. It is known that in certain regimes (e.g., when $r$ is of order $n^2$ and the allocation is asymptotically uniform as $n\to\infty$) the power divergence statistic converges in distribution to a linear transformation of a Poisson random variable. We establish explicit error bounds in the Kolmogorov (or uniform) metric to complement this convergence result, which may be applied for any values of $n$, $r$ and the index parameter $λ$ for which such a finite-sample bound is meaningful. We further use this Poisson approximation result to derive error bounds in Gaussian approximation of the power divergence statistics.

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Fraser Daly. 2023-11-16. Poisson and Gaussian approximations of the power divergence family of statistics. https://doi.org/10.30757/alea.v21-02

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