Adaptive Convergence Rates of a Dirichlet Process Mixture of Multivariate Normals

Surya T. Tokdar

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arXiv · 1111.4148

Adaptive Convergence Rates of a Dirichlet Process Mixture of Multivariate Normals

Surya T. Tokdar

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Abstract

It is shown that a simple Dirichlet process mixture of multivariate normals offers Bayesian density estimation with adaptive posterior convergence rates. Toward this, a novel sieve for non-parametric mixture densities is explored, and its rate adaptability to various smoothness classes of densities in arbitrary dimension is demonstrated. This sieve construction is expected to offer a substantial technical advancement in studying Bayesian non-parametric mixture models based on stick-breaking priors.

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Surya T. Tokdar. 2011-11-17. Adaptive Convergence Rates of a Dirichlet Process Mixture of Multivariate Normals. https://arxiv.org/abs/1111.4148

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