A generalized multiple-try version of the Reversible Jump algorithm
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DOI: 10.1016/j.csda.2013.10.007
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References listed on IDEAS
- David I. Hastie & Peter J. Green, 2012. "Model choice using reversible jump Markov chain Monte Carlo," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 309-338, August.
- 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.
- Ajay Jasra & David A. Stephens & Christopher C. Holmes, 2007. "Population-Based Reversible Jump Markov Chain Monte Carlo," Biometrika, Biometrika Trust, vol. 94(4), pages 787-807.
- Olivier Cappé & Christian P. Robert & Tobias Rydén, 2003. "Reversible jump, birth‐and‐death and more general continuous time Markov chain Monte Carlo samplers," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 65(3), pages 679-700, August.
- Liu, Rui-Yin & Tao, Jian & Shi, Ning-Zhong & He, Xuming, 2011. "Bayesian analysis of the patterns of biological susceptibility via reversible jump MCMC sampling," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1498-1508, March.
- Nial Friel & Jason Wyse, 2012. "Estimating the evidence – a review," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 66(3), pages 288-308, August.
- Francesco Bartolucci & Luisa Scaccia & Antonietta Mira, 2006. "Efficient Bayes factor estimation from the reversible jump output," Biometrika, Biometrika Trust, vol. 93(1), pages 41-52, March.
- Martino, Luca & Del Olmo, Victor Pascual & Read, Jesse, 2012. "A multi-point Metropolis scheme with generic weight functions," Statistics & Probability Letters, Elsevier, vol. 82(7), pages 1445-1453.
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Cited by:
- Mike K. P. So & Wing Ki Liu & Amanda M. Y. Chu, 2018. "Bayesian Shrinkage Estimation Of Time-Varying Covariance Matrices In Financial Time Series," Advances in Decision Sciences, Asia University, Taiwan, vol. 22(1), pages 369-404, December.
- Xin Luo & Håkon Tjelmeland, 2019. "A multiple-try Metropolis–Hastings algorithm with tailored proposals," Computational Statistics, Springer, vol. 34(3), pages 1109-1133, September.
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Keywords
Bayesian inference; Latent class model; Logistic model; Markov chain Monte Carlo; Metropolis–Hastings algorithm;All these keywords.
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