Markov Chain Monte Carlo conver-gence diagnostics: a comparative review
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[1] Bin Yu,et al. Regeneration in Markov chain samplers , 1995 .
[2] J. Q. Smith,et al. 1. Bayesian Statistics 4 , 1993 .
[3] A. Gelfand,et al. Efficient parametrisations for normal linear mixed models , 1995 .
[4] Jim Albert. Teaching Bayesian Statistics Using Sampling Methods and MINITAB , 1993 .
[5] Philip Heidelberger,et al. Simulation Run Length Control in the Presence of an Initial Transient , 1983, Oper. Res..
[6] James O. Berger,et al. Bayesian Estimation of Fuel Economy Potential Due to Technology Improvements , 1993 .
[7] Lee W. Schruben,et al. Detecting Initialization Bias in Simulation Output , 1982, Oper. Res..
[8] G. Casella,et al. Explaining the Gibbs Sampler , 1992 .
[9] A. Raftery,et al. How Many Iterations in the Gibbs Sampler , 1991 .
[10] V. Johnson. Studying Convergence of Markov Chain Monte Carlo Algorithms Using Coupled Sample Paths , 1996 .
[11] Walter R. Gilks,et al. BUGS - Bayesian inference Using Gibbs Sampling Version 0.50 , 1995 .
[12] M. Tanner,et al. Facilitating the Gibbs Sampler: The Gibbs Stopper and the Griddy-Gibbs Sampler , 1992 .
[13] Joong-Kweon Sohn,et al. Convergence Diagnostics for the Gibbs Sampler , 1996 .
[14] N. Best,et al. Convergence Diagnosis and Output Analysis Software for Gibbs sampling output Version 0.30 , 1995 .
[15] Brian D. Ripley,et al. Stochastic Simulation , 2005 .
[16] J. Rosenthal. Minorization Conditions and Convergence Rates for Markov Chain Monte Carlo , 1995 .
[17] J. Rosenthal. RATES OF CONVERGENCE FOR GIBBS SAMPLING FOR VARIANCE COMPONENT MODELS , 1995 .
[18] A. Gelfand,et al. Maximum-likelihood estimation for constrained- or missing-data models , 1993 .
[19] C. Buck,et al. Detecting a Change in the Shape of a Prehistoric Corbelled Tomb , 1993 .
[20] L. Mark Berliner,et al. Subsampling the Gibbs Sampler , 1994 .
[21] J. Besag,et al. Spatial Statistics and Bayesian Computation , 1993 .
[22] Bradley P. Carlin,et al. Hierarchical Bayes Models for the Progression of HIV Infection Using Longitudinal CD4+ Counts. , 1992 .
[23] Hani Doss. Discussion: Markov Chains for Exploring Posterior Distributions , 1994 .
[24] Peter Green,et al. Spatial statistics and Bayesian computation (with discussion) , 1993 .
[25] W. K. Hastings,et al. Monte Carlo Sampling Methods Using Markov Chains and Their Applications , 1970 .
[26] Lee W. Schruben,et al. Optimal Tests for Initialization Bias in Simulation Output , 1983, Oper. Res..
[27] A. Gelfand,et al. Hierarchical Bayes Models for the Progression of HIV Infection Using Longitudinal CD4 T-Cell Numbers , 1992 .
[28] Jim Albert,et al. A Bayesian Analysis of a Poisson Random Effects Model for Home Run Hitters , 1992 .
[29] L. Tierney. Markov Chains for Exploring Posterior Distributions , 1994 .
[30] W. Cleveland. Robust Locally Weighted Regression and Smoothing Scatterplots , 1979 .
[31] John Geweke,et al. Evaluating the accuracy of sampling-based approaches to the calculation of posterior moments , 1991 .
[32] L. Tierney. Rejoinder: Markov Chains for Exploring Posterior Distributions , 1994 .
[33] C. Geyer,et al. Annealing Markov chain Monte Carlo with applications to ancestral inference , 1995 .
[34] Jeffrey S. Rosenthal,et al. Analysis of the Gibbs Sampler for a Model Related to James-stein Estimators , 2007 .
[35] Charles J. Geyer,et al. Practical Markov Chain Monte Carlo , 1992 .
[36] Walter R. Gilks,et al. A Language and Program for Complex Bayesian Modelling , 1994 .
[37] N. Metropolis,et al. Equation of State Calculations by Fast Computing Machines , 1953, Resonance.
[38] Richard L. Tweedie,et al. Markov Chains and Stochastic Stability , 1993, Communications and Control Engineering Series.
[39] B. Carlin,et al. On the Convergence of Successive Substitution Sampling , 1992 .
[40] D. Rubin,et al. Inference from Iterative Simulation Using Multiple Sequences , 1992 .
[41] A. Gelfand,et al. On Markov Chain Monte Carlo Acceleration , 1994 .
[42] Wang,et al. Nonuniversal critical dynamics in Monte Carlo simulations. , 1987, Physical review letters.
[43] J. Rosenthal. Rates of Convergence for Data Augmentation on Finite Sample Spaces , 1993 .
[44] Donald Geman,et al. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.
[45] Donald B. Rubin,et al. [Practical Markov Chain Monte Carlo]: Rejoinder: Replication without Contrition , 1992 .
[46] A. Zellner,et al. Gibbs Sampler Convergence Criteria , 1995 .
[47] Adrian F. M. Smith,et al. Sampling-Based Approaches to Calculating Marginal Densities , 1990 .
[48] Martin A. Tanner,et al. Posterior Computations for Censored Regression Data , 1990 .
[49] K. Cowles,et al. CODA: convergence diagnosis and output analysis software for Gibbs sampling output , 1995 .
[50] M. Tanner,et al. [Practical Markov Chain Monte Carlo]: Comment: Monitoring Convergence of the Gibbs Sampler: Further Experience with the Gibbs Stopper , 1992 .
[51] C. Geyer,et al. Discussion: Markov Chains for Exploring Posterior Distributions , 1994 .