On rates of convergence for posterior distributions in infinite-dimensional models

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This paper introduces a new approach to the study of rates of convergence for posterior distributions. It is a natural extension of a recent approach to the study of Bayesian consistency. In particular, we improve on current rates of convergence for models including the mixture of Dirichlet process model and the random Bernstein polynomial model.
Published at http://dx.doi.org/10.1214/009053606000001361 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)

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Statistics Theory, 62G07, 62G20, 62F15 (Primary)

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http://salesiana.dossiersoluciones.com/handle/123456789/136400

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/0708.1892
 http://arxiv.org/abs/0708.1892
 Annals of Statistics 2007, Vol. 35, No. 2, 738-746
 doi:10.1214/009053606000001361

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