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Posterior convergence rate of a class of Dirichlet process mixture model for compositional data

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  • Barrientos, Andrés F.
  • Jara, Alejandro
  • Wehrhahn, Claudia

Abstract

We propose a Dirichlet process mixture of mixtures of Dirichlet models for density estimation. By assuming random sampling from a density belonging to a Hölder class, we show that the posterior distribution of the model is rate-optimal.

Suggested Citation

  • Barrientos, Andrés F. & Jara, Alejandro & Wehrhahn, Claudia, 2017. "Posterior convergence rate of a class of Dirichlet process mixture model for compositional data," Statistics & Probability Letters, Elsevier, vol. 120(C), pages 45-51.
    • Handle: RePEc:eee:stapro:v:120:y:2017:i:c:p:45-51
    DOI: 10.1016/j.spl.2016.09.008
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    References listed on IDEAS

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    1. Sonia Petrone, 1999. "Random Bernstein Polynomials," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 26(3), pages 373-393, September.
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