Abstract
In Gaussian sequence models with Gaussian priors, we develop some simple examples to illustrate three perspectives on matching of posterior and frequentist probabilities when the dimension p increases with sample size n: (i) convergence of joint posterior distributions, (ii) behavior of a non-linear functional: squared error loss, and (iii) estimation of linear functionals. The three settings are progressively less demanding in terms of conditions needed for validity of the Bernstein-von Mises theorem.
Information
Published: 1 January 2010
First available in Project Euclid: 26 October 2010
MathSciNet: MR2798513
Digital Object Identifier: 10.1214/10-IMSCOLL607
Subjects:
Primary:
62E20
Secondary:
62F15
Keywords:
frequentist
,
Gaussian sequence
,
High dimensional inference
,
linear functional
,
posterior distribution
,
squared error loss
Rights: Copyright © 2010, Institute of Mathematical Statistics