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- W2884747918 abstract "We establish two theorems for assessing the accuracy in total variation of multivariate discrete normal approximation to the distribution of an integer valued random vector $W$. The first is for sums of random vectors whose dependence structure is local. The second applies to random vectors~$W$ resulting from integrating the $mathbb{Z}^d$-valued marks of a marked point process with respect to its ground process. The error bounds are of magnitude comparable to those given in Rinott and Rotar (1996), but now with respect to the stronger total variation distance. Instead of requiring the summands to be bounded, we make third moment assumptions. We demonstrate the use of the theorems in four applications: monochrome edges in vertex coloured graphs, induced triangles and $2$-stars in random geometric graphs, the times spent in different states by an irreducible and aperiodic finite Markov chain, and the maximal points in different regions of a homogeneous Poisson point process." @default.
- W2884747918 created "2018-08-03" @default.
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- W2884747918 date "2018-07-17" @default.
- W2884747918 modified "2023-10-16" @default.
- W2884747918 title "Multivariate approximation in total variation using local dependence" @default.
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- W2884747918 doi "https://doi.org/10.48550/arxiv.1807.06715" @default.
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