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
21541993
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
16311997
Efficient metropolis jumping rules
A Gelman, G Roberts, W Gilks
Bayesian statistics 5, 599-608, 1996
12211996
Optimal scaling for various Metropolis-Hastings algorithms
GO Roberts, JS Rosenthal
Statistical science 16 (4), 351-367, 2001
10482001
Examples of adaptive MCMC
GO Roberts, JS Rosenthal
Journal of Computational and Graphical Statistics 18 (2), 349-367, 2009
8472009
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
8171997
Exponential convergence of Langevin distributions and their discrete approximations
GO Roberts, RL Tweedie
Bernoulli 2 (4), 341-363, 1996
6931996
The pseudo-marginal approach for efficient Monte Carlo computations
C Andrieu, GO Roberts
The Annals of Statistics 37 (2), 697-725, 2009
6772009
General state space Markov chains and MCMC algorithms
GO Roberts, JS Rosenthal
Probability surveys 1, 20-71, 2004
6662004
Optimal scaling of discrete approximations to Langevin diffusions
GO Roberts, JS Rosenthal
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 1998
5071998
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
4901997
Markov chain concepts related to sampling algorithms
GO Roberts
Markov chain Monte Carlo in practice 57, 45-58, 1996
4901996
Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms
GO Roberts, RL Tweedie
Biometrika 83 (1), 95-110, 1996
4471996
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
4241994
Coupling and ergodicity of adaptive Markov chain Monte Carlo algorithms
GO Roberts, JS Rosenthal
Journal of applied probability 44 (2), 458-475, 2007
4102007
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
3922006
Assessing convergence of Markov chain Monte Carlo algorithms
SP Brooks, GO Roberts
Statistics and Computing 8 (4), 319-335, 1998
3921998
Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models
O Papaspiliopoulos, GO Roberts
Biometrika 95 (1), 169-186, 2008
3752008
Strategies for improving MCMC
WR Gilks, GO Roberts
Markov chain Monte Carlo in practice 6, 89-114, 1996
3721996
Convergence assessment techniques for Markov chain Monte Carlo
SP Brooks, GO Roberts
Statistics and Computing 8 (4), 319-335, 1998
3711998
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