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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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hdl_136934.pdf | Published version | 221.18 kB | Adobe PDF | View/Open |
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