Gareth Roberts
Gareth Roberts
Professor of Statistics, University of Warwick
Verified email at warwick.ac.uk
Title
Cited by
Cited by
Year
Bayesian computation via the Gibbs sampler and related Markov chain Monte Carlo methods
AFM Smith, GO Roberts
Journal of the Royal Statistical Society: Series B (Methodological) 55 (1), 3-23, 1993
21861993
Weak convergence and optimal scaling of random walk Metropolis algorithms
GO Roberts, A Gelman, WR Gilks
The annals of applied probability 7 (1), 110-120, 1997
17371997
Efficient metropolis jumping rules
A Gelman, G Roberts, W Gilks
Bayesian statistics 5, 599-608, 1996
12791996
Optimal scaling for various Metropolis-Hastings algorithms
GO Roberts, JS Rosenthal
Statistical science 16 (4), 351-367, 2001
11272001
Examples of adaptive MCMC
GO Roberts, JS Rosenthal
Journal of Computational and Graphical Statistics 18 (2), 349-367, 2009
9142009
The EM algorithm—an old folk‐song sung to a fast new tune
XL Meng, D Van Dyk
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 1997
8571997
Exponential convergence of Langevin distributions and their discrete approximations
GO Roberts, RL Tweedie
Bernoulli 2 (4), 341-363, 1996
7491996
The pseudo-marginal approach for efficient Monte Carlo computations
C Andrieu, GO Roberts
The Annals of Statistics 37 (2), 697-725, 2009
7332009
General state space Markov chains and MCMC algorithms
GO Roberts, JS Rosenthal
Probability surveys 1, 20-71, 2004
7152004
Optimal scaling of discrete approximations to Langevin diffusions
GO Roberts, JS Rosenthal
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 1998
5381998
Updating schemes, correlation structure, blocking and parameterization for the Gibbs sampler
GO Roberts, SK Sahu
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 1997
5151997
Markov chain concepts related to sampling algorithms
GO Roberts
Markov chain Monte Carlo in practice 57, 45-58, 1996
5061996
Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
GO Roberts, RL Tweedie
Biometrika 83 (1), 95-110, 1996
4651996
Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms
GO Roberts, AFM Smith
Stochastic processes and their applications 49 (2), 207-216, 1994
4451994
Coupling and ergodicity of adaptive Markov chain Monte Carlo algorithms
GO Roberts, JS Rosenthal
Journal of applied probability 44 (2), 458-475, 2007
4382007
Exact and computationally efficient likelihood‐based estimation for discretely observed diffusion processes (with discussion)
A Beskos, O Papaspiliopoulos, GO Roberts, P Fearnhead
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2006
4052006
Assessing convergence of Markov chain Monte Carlo algorithms
SP Brooks, GO Roberts
Statistics and Computing 8 (4), 319-335, 1998
4041998
MCMC methods for functions: modifying old algorithms to make them faster
SL Cotter, GO Roberts, AM Stuart, D White
Statistical Science, 424-446, 2013
3932013
Convergence assessment techniques for Markov chain Monte Carlo
SP Brooks, GO Roberts
Statistics and Computing 8 (4), 319-335, 1998
3901998
Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models
O Papaspiliopoulos, GO Roberts
Biometrika 95 (1), 169-186, 2008
3862008
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