Posterior concentration rates for infinite dimensional exponential families

In this paper we derive adaptive non-parametric rates of concentration of the posterior distributions for the density model on the class of Sobolev and Besov spaces. For this purpose, we build prior models based on wavelet or Fourier expansions of the logarithm of the density. The prior models are not necessarily Gaussian

MoreLess

Year of publication:	2012
Authors:	Rivoirard, Vincent ; Rousseau, Judith
Institutions:	Université Paris-Dauphine (Paris IX)
Subject:	Sobolev balls \| Besov balls \| Bayesian non-parametric \| rates of convergence \| adaptive estimation \| wavelets \| Fourier Bases

Check Google Scholar |

More access options

In German libraries (KVK)

I need help

More details

Series:	Economics Papers from University Paris Dauphine.
Type of publication:	Book / Working Paper
Notes:	Published in Bayesian Analysis, 2012, Vol. 7, no. 2. pp. 311-334.Length: 23 pages
Classification:	C11 - Bayesian Analysis
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010861471