2000 character limit reached
Posterior contraction rates for deconvolution of Dirichlet-Laplace mixtures
Published 27 Jul 2015 in math.ST and stat.TH | (1507.07412v2)
Abstract: We study nonparametric Bayesian inference with location mixtures of the Laplace density and a Dirichlet process prior on the mixing distribution. We derive a contraction rate of the corresponding posterior distribution, both for the mixing distribution relative to the Wasserstein metric and for the mixed density relative to the Hellinger and $L_q$ metrics.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
Top Community Prompts
Collections
Sign up for free to add this paper to one or more collections.