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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Abstract

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

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

Dates
First available in Project Euclid: 12 April 2019

Permanent link to this document
https://projecteuclid.org/euclid.ss/1555056029

Digital Object Identifier
doi:10.1214/18-STS683

Mathematical Reviews number (MathSciNet)
MR3938962

Keywords
Computational statistics nonparametric statistics probabilistic numerics uncertainty quantification

Citation

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. https://projecteuclid.org/euclid.ss/1555056029


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See also

  • Main article: Probabilistic Integration: A Role in Statistical Computation?.