Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/136934
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Type: Journal article
Title: Rejoinder: Probabilistic integration: A role in statistical computation?
Author: Briol, F.X.
Oates, C.J.
Girolami, M.
Osborne, M.A.
Sejdinovic, D.
Citation: Statistical Science: a review journal, 2019; 34(1):38-42
Publisher: Institute of Mathematical Statistics
Issue Date: 2019
ISSN: 0883-4237
2168-8745
Statement of
Responsibility: 
François-Xavier Briol, Chris J. Oates, Mark Girolami, Michael A. Osborne and Dino Sejdinovic
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?
Keywords: Computational statistics; nonparametric statistics; probabilistic numerics; uncertainty quantification
Description: Main article: https://doi.org/10.1214/18-STS660
Rights: © Institute of Mathematical Statistics, 2019. Open Access
DOI: 10.1214/18-STS683
Grant ID: http://purl.org/au-research/grants/arc/CE140100049
Published version: http://dx.doi.org/10.1214/18-sts683
Appears in Collections:Mathematical Sciences publications

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