Open Access
February 2016 Rate exact Bayesian adaptation with modified block priors
Chao Gao, Harrison H. Zhou
Ann. Statist. 44(1): 318-345 (February 2016). DOI: 10.1214/15-AOS1368


A novel block prior is proposed for adaptive Bayesian estimation. The prior does not depend on the smoothness of the function or the sample size. It puts sufficient prior mass near the true signal and automatically concentrates on its effective dimension. A rate-optimal posterior contraction is obtained in a general framework, which includes density estimation, white noise model, Gaussian sequence model, Gaussian regression and spectral density estimation.


Download Citation

Chao Gao. Harrison H. Zhou. "Rate exact Bayesian adaptation with modified block priors." Ann. Statist. 44 (1) 318 - 345, February 2016.


Received: 1 August 2014; Revised: 1 July 2015; Published: February 2016
First available in Project Euclid: 10 December 2015

zbMATH: 1331.62215
MathSciNet: MR3449770
Digital Object Identifier: 10.1214/15-AOS1368

Primary: 62G07 , 62G20

Keywords: adaptive estimation , Bayesian nonparametrics , block prior

Rights: Copyright © 2016 Institute of Mathematical Statistics

Vol.44 • No. 1 • February 2016
Back to Top