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November 2016 Model Uncertainty First, Not Afterwards
Ingrid Glad, Nils Lid Hjort
Statist. Sci. 31(4): 490-494 (November 2016). DOI: 10.1214/16-STS559

Abstract

Watson and Holmes propose ways of investigating robustness of statistical decisions by examining certain neighbourhoods around a posterior distribution. This may partly amount to ad hoc modelling of extra uncertainty. Instead of creating neighbourhoods around the posterior a posteriori, we argue that it might be more fruitful to model a layer of extra uncertainty first, in the model building process, and then allow the data to determine how big the resulting neighbourhoods ought to be. We develop and briefly illustrate a general strategy along such lines.

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Ingrid Glad. Nils Lid Hjort. "Model Uncertainty First, Not Afterwards." Statist. Sci. 31 (4) 490 - 494, November 2016. https://doi.org/10.1214/16-STS559

Information

Published: November 2016
First available in Project Euclid: 19 January 2017

zbMATH: 06946238
MathSciNet: MR3598726
Digital Object Identifier: 10.1214/16-STS559

Keywords: envelopes , Kullback–Leibler distance , local neighbourhoods , model robustness

Rights: Copyright © 2016 Institute of Mathematical Statistics

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Vol.31 • No. 4 • November 2016
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