Bayesian multivariate Bernstein polynomial density estimation

This paper introduces a new approach to Bayesian nonparametric inference for densities on the hypercube, based on the use of a multivariate Bernstein polynomial prior. Posterior convergence rates under the proposed prior are obtained. Furthermore, a novel sampling scheme, based on the use of slice sampling techniques, is proposed for estimation of the posterior predictive density. The approach is illustrated with both simulated and real data examples

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Year of publication:	2013-06
Authors:	Zhao, Yanyun ; Ausín, Concepción ; Wiper, Michael P.
Institutions:	Departamento de Estadistica, Universidad Carlos III de Madrid
Subject:	Bayesian nonparametrics \| Bernstein polynomials \| Dirichlet process

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Extent:	application/pdf
Series:	Statistics and Econometrics Working Papers.
Type of publication:	Book / Working Paper
Source:	RePEc - Research Papers in Economics

Persistent link: https://ebvufind01.dmz1.zbw.eu/10010659129