Open Access
Translator Disclaimer
april 1999 Asymptotic normality of posterior distributions in high-dimensional linear models
Subhashis Ghosal
Author Affiliations +
Bernoulli 5(2): 315-331 (april 1999).

Abstract

We study consistency and asymptotic normality of posterior distributions of the regression coefficient in a linear model when the dimension of the parameter grows with increasing sample size. Under certain growth restrictions on the dimension (depending on the design matrix), we show that the posterior distributions concentrate in neighbourhoods of the true parameter and can be approximated by an appropriate normal distribution.

Citation

Download Citation

Subhashis Ghosal. "Asymptotic normality of posterior distributions in high-dimensional linear models." Bernoulli 5 (2) 315 - 331, april 1999.

Information

Published: april 1999
First available in Project Euclid: 5 March 2007

zbMATH: 0948.62007
MathSciNet: MR1681701

Keywords: high dimension , linear model , Normal approximation , posterior consistency , posterior distribution

Rights: Copyright © 1999 Bernoulli Society for Mathematical Statistics and Probability

JOURNAL ARTICLE
17 PAGES


SHARE
Vol.5 • No. 2 • april 1999
Back to Top