Posterior consistency of Dirichlet mixtures for estimating a transition density

@inproceedings{Tanga2005PosteriorCO,
  title={Posterior consistency of Dirichlet mixtures for estimating a transition density},
  author={Yongqiang Tanga and Subhashis Ghosalb},
  year={2005}
}
  • Yongqiang Tanga, Subhashis Ghosalb
  • Published 2005
The Dirichlet process mixture of normal densities has been successfully used as a prior for Bayesian density estimation for independent and identically distributed (i.i.d.) observations. A Markov model, which generalizes the i.i.d. set up, may be thought of as a suitable framework for observations arising over time. The predictive density of the future observation is then given by the posterior expectation of the transition density given the observations. We consider a Dirichlet process mixture… CONTINUE READING
Highly Cited
This paper has 18 citations. REVIEW CITATIONS

From This Paper

Topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 13 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 15 references

Markov Chains and Stochastic Stability

  • S. P. Meyn, R. L. Tweedie
  • 1993
Highly Influential
4 Excerpts

Robust testing for independent non identically distributed variables and Markov chains

  • L. Birgé
  • Lecture Notes in Statistics,
  • 1983
Highly Influential
6 Excerpts

Density estimation for Markov processes using delta-sequences

  • B.L.S. Prakasa Rao
  • An. Inst. Statist. Math
  • 1978
Highly Influential
5 Excerpts

Dirichlet process mixture models for Markov processes

  • Y. Tang
  • Unpublished Ph.D. Thesis,
  • 2003
Highly Influential
2 Excerpts

On Bayes procedures

  • L. Schwartz
  • Z. Wahr. Verw. Gebiete
  • 1965
Highly Influential
2 Excerpts

On sufficient conditions for Bayesian consistency

  • Y. Tang, S. Ghosal
  • Journal of Statistical Planning and Inference
  • 2007

Similar Papers

Loading similar papers…