Reply to Robert et al.: Model criticism informs model choice and model comparison

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Title: Reply to Robert et al.: Model criticism informs model choice and model comparison
Author(s): Ratmann, O
Andrieu, C
Wiuf, C
Richardson, S
Item Type: Journal Article
Abstract: In their letter to PNAS and a comprehensive set of notes on arXiv [arXiv:0909.5673v2], Christian Robert, Kerrie Mengersen and Carla Chen (RMC) represent our approach to model criticism in situations when the likelihood cannot be computed as a way to "contrast several models with each other". In addition, RMC argue that model assessment with Approximate Bayesian Computation under model uncertainty (ABCmu) is unduly challenging and question its Bayesian foundations. We disagree, and clarify that ABCmu is a probabilistically sound and powerful too for criticizing a model against aspects of the observed data, and discuss further the utility of ABCmu.
Publication Date: 14-Jan-2010
Date of Acceptance: 1-Jan-2010
URI: http://hdl.handle.net/10044/1/52170
DOI: https://dx.doi.org/10.1073/pnas.0912887107
ISSN: 0027-8424
Publisher: National Academy of Sciences
Start Page: E6
End Page: E7
Journal / Book Title: Proceedings of the National Academy of Sciences of the United States of America
Volume: 107
Issue: 3
Copyright Statement: © the authors
Sponsor/Funder: Wellcome Trust
Wellcome Trust
Funder's Grant Number: 069962/Z/02/Z
078324/Z/05/Z
Keywords: stat.ME
stat.ME
stat.ME
stat.ME
MD Multidisciplinary
Publication Status: Published
Open Access location: https://arxiv.org/pdf/0912.3182v1.pdf
Appears in Collections:Mathematics
Statistics
Faculty of Natural Sciences
Epidemiology, Public Health and Primary Care



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