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Stein's method, information theory and Bayesian statistics

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In this talk, I will first describe a new general approach to the celebrated Stein method for asymptotic approximations and apply it to diverse approximation problems. Then I will show how Stein’s method can be successfully used in two a priori unrelated domains, namely information theory and Bayesian statistics.

This talk is based on joint work with Gesine Reinert (University of Oxford) and Yvik Swan (Université de Liège).

This talk is part of the Statistics series.

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Average on Sundays: 7236.86324786 kWh Seminar Rooms, Strangeways Research Laboratory, Worts Causeway, CB18RN Department of Engineering

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