Statistical Science

Rejoinder: Probabilistic Integration: A Role in Statistical Computation?

François-Xavier Briol, Chris J. Oates, Mark Girolami, Michael A. Osborne, and Dino Sejdinovic

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This article is the rejoinder for the paper “Probabilistic Integration: A Role in Statistical Computation?” (Statist. Sci. 34 (2019) 1–22). We would first like to thank the reviewers and many of our colleagues who helped shape this paper, the Editor for selecting our paper for discussion, and of course all of the discussants for their thoughtful, insightful and constructive comments. In this rejoinder, we respond to some of the points raised by the discussants and comment further on the fundamental questions underlying the paper: (i) Should Bayesian ideas be used in numerical analysis? and (ii) If so, what role should such approaches have in statistical computation?

Article information

Statist. Sci., Volume 34, Number 1 (2019), 38-42.

First available in Project Euclid: 12 April 2019

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Computational statistics nonparametric statistics probabilistic numerics uncertainty quantification


Briol, François-Xavier; Oates, Chris J.; Girolami, Mark; Osborne, Michael A.; Sejdinovic, Dino. Rejoinder: Probabilistic Integration: A Role in Statistical Computation?. Statist. Sci. 34 (2019), no. 1, 38--42. doi:10.1214/18-STS683.

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