Article (Scientific journals)
Quantification of the impact of priors in Bayesian statistics via Stein's Method
Ghaderinezhad, Fatemeh; LEY, Christophe
2019In Statistics and Probability Letters, 146, p. 206 - 212
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Keywords :
Conjugate prior; Jeffreys’ prior; Stein's Method; Wasserstein distance; Statistics and Probability; Statistics, Probability and Uncertainty
Abstract :
[en] We compare two distinct non-uniform choices of prior distributions by quantifying the Wasserstein distance between the respective resulting posterior distributions at any fixed sample size by means of Stein's Method. We illustrate this measure of the prior impact on the normal, Binomial and Poisson models.
Disciplines :
Mathematics
Author, co-author :
Ghaderinezhad, Fatemeh;  Ghent University, Department of Applied Mathematics, Computer Science and Statistics, Ghent, Belgium
LEY, Christophe ;  University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Mathematics (DMATH) ; Ghent University, Department of Applied Mathematics, Computer Science and Statistics, Ghent, Belgium
External co-authors :
yes
Language :
English
Title :
Quantification of the impact of priors in Bayesian statistics via Stein's Method
Publication date :
March 2019
Journal title :
Statistics and Probability Letters
ISSN :
0167-7152
Publisher :
Elsevier B.V.
Volume :
146
Pages :
206 - 212
Peer reviewed :
Peer Reviewed verified by ORBi
Funders :
Ghent University
Funding text :
We would like to thank the Associate Editor as well as two anonymous reviewers for helpful comments that led to an improvement of the present paper. This research is supported by a BOF Starting Grant of of Ghent University .
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