Automatically tuned general-purpose MCMC via new adaptive diagnostics

[1]  W. K. Yuen,et al.  Optimal scaling of random walk Metropolis algorithms with discontinuous target densities , 2012, 1210.5090.

[2]  G. Fort,et al.  Convergence of adaptive and interacting Markov chain Monte Carlo algorithms , 2011, 1203.3036.

[3]  Matti Vihola,et al.  Robust adaptive Metropolis algorithm with coerced acceptance rate , 2010, Statistics and Computing.

[4]  Karline Soetaert,et al.  Inverse Modelling, Sensitivity and Monte Carlo Analysis in R Using Package FME , 2010 .

[5]  Andrew Thomas,et al.  The BUGS project: Evolution, critique and future directions , 2009, Statistics in medicine.

[6]  Gareth O. Roberts,et al.  Examples of Adaptive MCMC , 2009 .

[7]  Matti Vihola,et al.  Grapham: Graphical models with adaptive random walk Metropolis algorithms , 2008, Comput. Stat. Data Anal..

[8]  P. Giordani,et al.  Adaptive Independent Metropolis–Hastings by Fast Estimation of Mixtures of Normals , 2008, 0801.1864.

[9]  Anne-Mette K. Hein,et al.  BGX: a Bioconductor package for the Bayesian integrated analysis of Affymetrix GeneChips , 2007, BMC Bioinformatics.

[10]  Jeffrey S. Rosenthal,et al.  AMCMC: An R interface for adaptive MCMC , 2007, Comput. Stat. Data Anal..

[11]  J. Rosenthal,et al.  Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms , 2007, Journal of Applied Probability.

[12]  J. Rosenthal,et al.  General state space Markov chains and MCMC algorithms , 2004, math/0404033.

[13]  J. Rosenthal,et al.  Optimal scaling for various Metropolis-Hastings algorithms , 2001 .

[14]  H. Haario,et al.  An adaptive Metropolis algorithm , 2001 .

[15]  Andrew Gelman,et al.  General methods for monitoring convergence of iterative simulations , 1998 .

[16]  D. Rubin,et al.  Inference from Iterative Simulation Using Multiple Sequences , 1992 .

[17]  Adrian F. M. Smith,et al.  Sampling-Based Approaches to Calculating Marginal Densities , 1990 .

[18]  D. Gaver,et al.  Robust empirical bayes analyses of event rates , 1987 .

[19]  N. Metropolis,et al.  Equation of State Calculations by Fast Computing Machines , 1953, Resonance.

[20]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[21]  Radford M. Neal.  Optimal Proposal Distributions and Adaptive MCMC , 2011 .

[22]  A. F. Smith,et al.  Conjugate likelihood distributions , 1993 .