Rates of convergence for multivariate normal approximation with applications to dense graphs and doubly indexed permutation statistics

Xiao Fang; Adrian Röllin

doi:10.3150/14-bej639

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arXiv · 1206.6586

Rates of convergence for multivariate normal approximation with applications to dense graphs and doubly indexed permutation statistics

Xiao Fang·Adrian Röllin

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Abstract

We provide a new general theorem for multivariate normal approximation on convex sets. The theorem is formulated in terms of a multivariate extension of Stein couplings. We apply the results to a homogeneity test in dense random graphs and to prove multivariate asymptotic normality for certain doubly indexed permutation statistics.

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Xiao Fang, Adrian Röllin. 2015-09-18. Rates of convergence for multivariate normal approximation with applications to dense graphs and doubly indexed permutation statistics. https://doi.org/10.3150/14-bej639

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