Bayesian mixture of parametric and nonparametric density estimation: A Misspecification Problem
In this paper we study the effect of model misspecifications for probability density func tion estimation. We use a mixture of a parametric and nonparametric density estima tion. The former can be modeled by any suitable parametric probability density function, including mixture of parametric models...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2011 |
| País: | Brasil |
| Institución: | Instituição de Ensino Superior e de Pesquisa (INSPER) |
| Repositorio: | Repositório Institucional da INSPER |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.insper.edu.br:11224/4042 |
| Acceso en línea: | https://repositorio.insper.edu.br/handle/11224/4042 https://doi.org/10.12660/bre.v31n12011.4134 |
| Access Level: | acceso abierto |
| Palabra clave: | Nonparametric Density Estimation B-Splines Mixtures Models MCMC EM-Algortihm |
| Sumario: | In this paper we study the effect of model misspecifications for probability density func tion estimation. We use a mixture of a parametric and nonparametric density estima tion. The former can be modeled by any suitable parametric probability density function, including mixture of parametric models. The latter is given by the known B-spline es timation. The procedure also deals with the situation when a highly structured data are collected so that it is difficult to propose a parametric model with a large number of mixture components. Then a nonparametric part would help to postulate an appropriate model. In addition, in order to reduce the computational cost of getting a nonparamet ric density for high dimensional data a parametric mixture of densities could be used as the starting point for modeling such dataset. Our procedure is computed by using EM-type algorithm for a non-Bayesian approach and MCMC algorithm under a Bayesian point of view. Simulations and real data analysis show that our proposed procedure have performed quite well even for non structured datasets. |
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