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  Monte Carlo Statistical Methods (1999) [309 citations — 11 self]

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by Christian P. Robert
http://www.ensae.fr/crest/statistique/robert/MCMC.ps.gz
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Abstract:

Until the advent of powerful and accessible computing methods, the experimenter was confronted with a difficult choice. Either describe an accurate model of a phenomenon, which would usually prevent the computation

Citations

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54 Spatial statistics and Bayesian computation (with Discussion – Besag, Green - 1993
48 Towards Bayesian image analysis – Besag - 1989
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38 Bayesian Inference via Gibbs Sampling of Autoregressive Time Series Subject to Markov Mean and Variance Shifts – Albert, Chib - 1993
28 Asymptotic techniques for use in statistics – Barndorff-Nielsen, Cox - 1989
27 On a formula for the distribution of the maximum-likelihood estimator – Barndorff-Nielsen - 1983
26 An overview of robust Bayesian analysis (with discussion – Berger - 1994
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17 Computer methods for sampling from gamma, beta, Poisson, and binomial distributions – Ahrens, Ahrens, et al. - 1974
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10 A reversible jump MCMC sampler for Bayesian analysis of ARMA time series – Barbieri, O'Hagan - 1996
10 A Bayesian analysis of simple mixture problems – Bernardo, Giron - 1988
7 Computational methods using a Bayesian hierarchical generalized linear model – Albert - 1988
7 Parameter estimation for hidden Markov chains – Archer, Titterington - 2000
6 The Weighted Bootstrap – Barbe, Bertail - 1995
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1 Bayesian Full Information of Simultaneous Equations Models Using Integration by Monte Carlo – Bauwens - 1984
1 Estimation of quadratuc functions: reference priors for non-centrality parameters – Berger, Philippe, et al. - 1996
1 Discussion of "Markov chains for exploring posterior distributions – Besag - 1994
1 Meta-Analysis via Markov Chain MonteCarlo methods – Besag, Mengersen - 1993