Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1150127 | Journal of Statistical Planning and Inference | 2011 | 7 Pages |
Abstract
We investigate the posterior rate of convergence for wavelet shrinkage using a Bayesian approach in general Besov spaces. Instead of studying the Bayesian estimator related to a particular loss function, we focus on the posterior distribution itself from a nonparametric Bayesian asymptotics point of view and study its rate of convergence. We obtain the same rate as in Abramovich et al. (2004) where the authors studied the convergence of several Bayesian estimators.
Keywords
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Heng Lian,