On perfect simulation for some mixtures of distributions

Statistics and Computing

Volumn 9, Issue 4, 1999, Pages 287-298

  Hobert, James P ^a   Robert, Christian P ^b   Titterington, D M ^c  

^a University of Florida ^*  (United States)

^b UNIVERSITÉ DE ROUEN   (France)

^c UNIVERSITY OF GLASGOW   (United Kingdom)

Author keywords

Coupling; Gamma decomposition; Gibbs sampling; Monotonicity

Indexed keywords

EID: 0043047930     PISSN: 09603174     EISSN: None     Source Type: Journal    
DOI: 10.1023/A:1008912006771     Document Type: Article

References (12)

1. Diebolt, J. and Robert, C. P. (1994) Estimation of finite mixture distributions by Bayesian sampling. J. Royal Statist. Soc. (Ser. B), 56, 363-375.
2. Fill, J. A. (1998) An interruptible algorithm for perfect sampling via Markov chains. Ann. Applied Prob., 8, 131-162.
3. Green, P. J. and Murdoch, D. J. (1999) Exact sampling for Bayesian inference: towards general purpose algorithms. In Bernardo, J. M., Berger, J. O., Dawid, A. P. and Smith, A. F. M. (eds.) Bayesian Statistics 6, Oxford University Press, 301-322 (with Discussion).
4. Häggström, O., van Lieshout, M. N. M. and Møller, J. (1999) Characterisation results and Markov chain Monte Carlo algorithms including exact simulation for some spatial point processes. Bernoulli, vol. 5.
5. Kendall, W. (1998) Perfect simulation for the area-interaction point process. In Heyde, C. C. and Accardi, L. (eds) Probability Perspective, World Scientific Press, (to appear).
6. Liu, J. S., Liang, F. and Wong, W. H. (1998) The use of multiple-try method and local optimization in Metropolis sampling. Tech. report, Dept. of Statistics, Stanford University.
7. Møller, J. (1999) Perfect simulation of conditionally specified models. J. Royal Statist. Soc. (Ser. B), 61, 251-264.
8. Murdoch, D. J. and Green, P. J. (1998) Exact sampling from a continuous state space. Scand. J. Statist., 25, 483-502.
9. Propp, J. G. and Wilson, D. B. (1996) Exact sampling with coupled Markov chains and applications to statistical mechanics. Random Structures and Algorithms, 9, 223-252.
10. Propp, J. G. and Wilson, D. B. (1998) How to get a perfectly random sample from a generic Markov chain and generate a random spanning tree of a directed graph. J. Algorithms, 27, 170-217.
11. Robert, C. P. (1996) Inference in mixture models. In Gilks, W. R., Richardson, S. and Spiegelhalter, D. J. (eds.) Markov Chain Monte Carlo in Practice, pp. 441-464. Chapman and Hall, London.
12. Wilson, D. B. (1998) Annotated bibliography of perfectly random sampling with Markov chains. In Aldous, D. and Propp, J. (eds) Microsurveys in Discrete Probability, volume 41 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, 209-220.