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A practical sampling approach for a Bayesian mixture model with unknown number of components

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  • Liqun Wang
  • James Fu

Abstract

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  • Liqun Wang & James Fu, 2007. "A practical sampling approach for a Bayesian mixture model with unknown number of components," Statistical Papers, Springer, vol. 48(4), pages 631-653, October.
  • Handle: RePEc:spr:stpapr:v:48:y:2007:i:4:p:631-653
    DOI: 10.1007/s00362-007-0361-4
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    References listed on IDEAS

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    1. S. P. Brooks & P. Giudici & G. O. Roberts, 2003. "Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(1), pages 3-39, January.
    2. Matthew Stephens, 2000. "Dealing with label switching in mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 795-809.
    3. James C. Fu & Liqun Wang, 2002. "A Random-Discretization Based Monte Carlo Sampling Method and its Applications," Methodology and Computing in Applied Probability, Springer, vol. 4(1), pages 5-25, March.
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    Cited by:

    1. Wang, Liqun & Lee, Chel Hee, 2014. "Discretization-based direct random sample generation," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 1001-1010.

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