Article ID Journal Published Year Pages File Type
1150127 Journal of Statistical Planning and Inference 2011 7 Pages PDF
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.
Related Topics
Physical Sciences and Engineering Mathematics Applied Mathematics
Authors
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