Bayesian multivariate Bernstein polynomial density estimation
AbstractThis 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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Bibliographic InfoPaper provided by Universidad Carlos III, Departamento de Estadística y Econometría in its series Statistics and Econometrics Working Papers with number ws131211.
Date of creation: Jun 2013
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Bayesian nonparametrics; Bernstein polynomials; Dirichlet process;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-05-24 (All new papers)
- NEP-ECM-2013-05-24 (Econometrics)
- NEP-FOR-2013-05-24 (Forecasting)
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