Talk
in
Workshop: Stein’s Method for Machine Learning and Statistics

Invited Talk - Louis Chen: Palm theory, random measures and Stein couplings.

Louis Chen

2019 Talk
in
Workshop: Stein’s Method for Machine Learning and Statistics

Abstract

In this talk, we present a general Kolmogorov bound for normal approximation, proved using Stein’s method. We will apply this bound to random measures using Palm theory and coupling, with applications to stochastic geometry. We will also apply this bound to Stein couplings, which include local dependence, exchangeable pairs, size-bias couplings and more as special cases. This talk is based on joint work with Adrian Roellin and Aihua Xia.

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