Gareth Roberts

Q: What Schools Are Affiliated With Gareth Roberts

Gareth Roberts is affiliated with the following schools: University of Warwick, University of Nottingham, University of Oxford, Lancaster University, University of Cambridge

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Gareth Roberts

Mathematics

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Statistics

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World Rank

#271

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Mathematics

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According to Wikipedia, Gareth Owen Roberts FRS FLSW is a statistician and applied probabilist. He is Professor of Statistics in the Department of Statistics and Director of the Centre for Research in Statistical Methodology at the University of Warwick. He is an established authority on the stability of Markov chains, especially applied to Markov chain Monte Carlo theory methodology for a wide range of latent statistical models with applications in spatial statistics, infectious disease epidemiology and finance.

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Gareth Roberts 's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Bayesian computation via the gibbs sampler and related markov chain monte carlo methods (with discus (1993) (1751)
Weak convergence and optimal scaling of random walk Metropolis algorithms (1997) (1713)
Optimal scaling for various Metropolis-Hastings algorithms (2001) (1106)
Examples of Adaptive MCMC (2009) (994)
Exponential convergence of Langevin distributions and their discrete approximations (1996) (966)
The pseudo-marginal approach for efficient Monte Carlo computations (2009) (846)
General state space Markov chains and MCMC algorithms (2004) (780)
Optimal scaling of discrete approximations to Langevin diffusions (1998) (648)
MCMC Methods for Functions: ModifyingOld Algorithms to Make Them Faster (2012) (526)
Convergence assessment techniques for Markov chain Monte Carlo (1998) (457)
Geometric convergence and central limit theorems for multidimensional Hastings and Metropolis algorithms (1996) (446)
Updating Schemes, Correlation Structure, Blocking and Parameterization for the Gibbs Sampler (1997) (438)
Networks and the Epidemiology of Infectious Disease (2010) (409)
Exact and computationally efficient likelihood‐based estimation for discretely observed diffusion processes (with discussion) (2006) (404)
Markov chain Monte Carlo (2006) (401)
Coupling and Ergodicity of Adaptive Markov Chain Monte Carlo Algorithms (2007) (389)
Simple conditions for the convergence of the Gibbs sampler and Metropolis-Hastings algorithms (1994) (386)
Retrospective Markov chain Monte Carlo methods for Dirichlet process hierarchical models (2007) (377)
Geometric Ergodicity and Hybrid Markov Chains (1997) (354)
Link analysis ranking: algorithms, theory, and experiments (2005) (343)
Adaptive Markov Chain Monte Carlo through Regeneration (1998) (330)
Bayesian inference for partially observed stochastic epidemics (1999) (330)
On inference for partially observed nonlinear diffusion models using the Metropolis–Hastings algorithm (2001) (319)
Efficient construction of reversible jump Markov chain Monte Carlo proposal distributions (2003) (313)
Strategies for improving MCMC (1995) (290)
Optimal tuning of the hybrid Monte Carlo algorithm (2010) (288)
Exact simulation of diffusions (2005) (288)
Finding authorities and hubs from link structures on the World Wide Web (2001) (284)
Langevin Diffusions and Metropolis-Hastings Algorithms (2002) (281)
A General Framework for the Parametrization of Hierarchical Models (2007) (266)
Retrospective exact simulation of diffusion sample paths with applications (2006) (242)
The Zig-Zag process and super-efficient sampling for Bayesian analysis of big data (2016) (205)
Adaptive Direction Sampling (1994) (205)
A dynamic model of bovine tuberculosis spread and control in Great Britain (2014) (199)
On the efficiency of pseudo-marginal random walk Metropolis algorithms (2013) (187)
MCMC methods for diffusion bridges (2008) (184)
Polynomial convergence rates of Markov chains. (2002) (168)
Particle filters for partially observed diffusions (2007) (164)
Convergence of Slice Sampler Markov Chains (1999) (145)
Markov‐chain monte carlo: Some practical implications of theoretical results (1998) (139)
Bayesian inference for non‐Gaussian Ornstein–Uhlenbeck stochastic volatility processes (2004) (138)
Robust Markov chain Monte Carlo Methods for Spatial Generalized Linear Mixed Models (2006) (135)
Bayesian analysis for emerging infectious diseases (2009) (131)
On the Geometric Convergence of the Gibbs Sampler (1994) (130)
A Factorisation of Diffusion Measure and Finite Sample Path Constructions (2008) (117)
Bayesian non‐parametric hidden Markov models with applications in genomics (2011) (114)
Optimal scalings for local Metropolis--Hastings chains on nonproduct targets in high dimensions (2009) (108)
Scaling limits for the transient phase of local Metropolis–Hastings algorithms (2005) (108)
Corrigendum to : Bounds on regeneration times and convergence rates for Markov chains (2001) (107)
Harris recurrence of Metropolis-within-Gibbs and trans-dimensional Markov chains (2006) (105)
Towards optimal scaling of metropolis-coupled Markov chain Monte Carlo (2011) (103)
The Random Walk Metropolis: Linking Theory and Practice Through a Case Study (2010) (102)
Exponential Convergence of Langevin Diiusions and Their Discrete Approximations (1997) (95)
Geometric L 2 and L 1 convergence are equivalent for reversible Markov chains (2001) (91)
Piecewise Deterministic Markov Processes for Continuous-Time Monte Carlo (2016) (91)
Non-centred parameterisations for hierarchical models and data augmentation. (2003) (89)
Monte Carlo Maximum Likelihood Estimation for Discretely Observed Diffusion Processes (2009) (88)
Statistical inference and model selection for the 1861 Hagelloch measles epidemic. (2004) (86)
SUBGEOMETRIC ERGODICITY OF STRONG MARKOV PROCESSES (2005) (85)
Perfect slice samplers (2001) (82)
OPTIMAL SCALING FOR PARTIALLY UPDATING MCMC ALGORITHMS (2006) (81)
Adaptive Gibbs samplers and related MCMC methods (2011) (81)
Optimal scaling of the random walk Metropolis on elliptically symmetric unimodal targets (2009) (80)
Predicting undetected infections during the 2007 foot-and-mouth disease outbreak (2009) (78)
Rates of convergence of stochastically monotone and continuous time Markov models (2000) (76)
Bounds on regeneration times and convergence rates for Markov chains fn1 fn1 Work supported in part (1999) (74)
Nonparametric estimation of diffusions: a differential equations approach (2012) (74)
Weak convergence of conditioned processes on a countable state space (1995) (72)
Markov Chains and De‐initializing Processes (2001) (70)
On the containment condition for adaptive Markov chain Monte Carlo algorithms (2009) (70)
A piecewise deterministic scaling limit of Lifted Metropolis-Hastings in the Curie-Weiss model (2015) (69)
Convergence Properties of Perturbed Markov Chains (1998) (67)
A case study in non-centering for data augmentation: Stochastic epidemics (2005) (66)
Quantitative Bounds for Convergence Rates of Continuous Time Markov Processes (1996) (65)
Convergence of Heavy‐tailed Monte Carlo Markov Chain Algorithms (2007) (64)
Convergence of adaptive direction sampling (1994) (62)
Random‐weight particle filtering of continuous time processes (2010) (60)
Variance bounding Markov chains. (2008) (60)
Ergodicity of the zigzag process (2017) (56)
Possible biases induced by MCMC convergence diagnostics (1999) (56)
A novel approach to real-time risk prediction for emerging infectious diseases: a case study in Avian Influenza H5N1. (2009) (55)
On the geometric ergodicity of hybrid samplers (2003) (53)
From metropolis to diffusions: Gibbs states and optimal scaling (2000) (52)
Stability of the Gibbs sampler for Bayesian hierarchical models (2007) (52)
Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains (2017) (50)
Two convergence properties of hybrid samplers (1998) (49)
On convergence of the EM algorithmand the Gibbs sampler (1999) (46)
Shift-coupling and convergence rates of ergodic averages (1997) (45)
Bayesian Inference For Nondecomposable Graphical Gaussian Models. (2003) (44)
On the exact and ε-strong simulation of (jump) diffusions (2013) (43)
Optimal scaling of random walk Metropolis algorithms with discontinuous target densities (2012) (43)
Exact Simulation of Jump-Diffusion Processes with Monte Carlo Applications (2011) (42)
Kinetic energy choice in Hamiltonian/hybrid Monte Carlo (2017) (41)
A quasi-ergodic theorem for evanescent processes (1999) (39)
Simulating events of unknown probabilities via reverse time martingales (2009) (39)
Bayes factors for discrete observations from diffusion processes (1994) (38)
Markov Chain Monte Carlo for Exact Inference for Diffusions (2011) (38)
Stability of noisy Metropolis–Hastings (2015) (37)
Minimising MCMC variance via diffusion limits, with an application to simulated tempering (2014) (37)
An Introduction to MCMC (2003) (36)
Bayesian Nonparametric Hidden Markov Models with application to the analysis of copy-number-variation in mammalian genomes. (2011) (36)
Inference for stochastic volatility model using time change transformations (2007) (35)
An Approach to Diagnosing Total Variation Convergence of MCMC Algorithms (1997) (35)
Markov chain Monte Carlo methods for switching diffusion models (2001) (35)
Optimal Scaling for Random Walk Metropolis on Spherically Constrained Target Densities (2008) (34)
Data Augmentation for Diffusions (2013) (33)
On convergence rates of Gibbs samplers for uniform distributions (1998) (32)
Importance sampling techniques for estimation of diffusions models (2009) (32)
Scalable importance tempering and Bayesian variable selection (2018) (31)
An adaptive approach to Langevin MCMC (2012) (31)
Linking theory and practice of MCMC. (2003) (30)
A note on acceptance rate criteria for CLTS for Metropolis–Hastings algorithms (1999) (29)
The Scalable Langevin Exact Algorithm : Bayesian Inference for Big Data (2016) (29)
Catalytic Perfect Simulation (2001) (28)
The polar slice sampler (2002) (27)
Convergence of Conditional Metropolis-Hastings Samplers (2014) (26)
Fast Langevin based algorithm for MCMC in high dimensions (2015) (26)
High-dimensional scaling limits of piecewise deterministic sampling algorithms (2018) (26)
SMALL AND PSEUDO-SMALL SETS FOR MARKOV CHAINS (2001) (25)
One-shot coupling for certain stochastic recursive sequences (2002) (25)
Exact Simulation Problems for Jump-Diffusions (2014) (25)
Markov Chain Monte Carlo Methods (2006) (25)
An MCMC method for diffusion bridges (2008) (24)
Downweighting tightly knit communities in world wide web ranking. (2003) (24)
On strong forms of weak convergence (1997) (24)
Scalable inference for crossed random effects models (2018) (24)
Exact Monte Carlo simulation of killed diffusions (2008) (23)
The Boomerang Sampler (2020) (23)
Complexity bounds for Markov chain Monte Carlo algorithms via diffusion limits (2016) (23)
Optimal metropolis algorithms for product measures on the vertices of a hypercube (1998) (22)
Surprising Convergence Properties of Some Simple Gibbs Samplers under Various Scans (2015) (22)
Quantitative Non-Geometric Convergence Bounds for Independence Samplers (2011) (21)
Unbiased Monte Carlo: Posterior estimation for intractable/infinite-dimensional models (2014) (21)
CLTs and Asymptotic Variance of Time-Sampled Markov Chains (2011) (20)
ε-Strong simulation of the Brownian path (2011) (20)
Weight-preserving simulated tempering (2018) (20)
Assessing Convergence of Markov Chain MonteCarlo (1997) (19)
Optimal Scaling of Random Walk Metropolis Algorithms with Non-Gaussian Proposals (2011) (19)
Weak convergence of conditioned birth and death processes (1994) (19)
A note on geometric ergodicity and floating-point roundoff error (2001) (19)
Stability of adversarial Markov chains, with an application to adaptive MCMC algorithms (2014) (18)
Optimal scaling of random-walk metropolis algorithms on general target distributions (2019) (18)
Extremal indices, geometric ergodicity of Markov chains, and MCMC (2006) (17)
The Hazard Rate Tangent Approximation for Boundary Hitting Times (1995) (17)
Systematic physics constrained parameter estimation of stochastic differential equations (2013) (17)
Asymptotic Approximations for Brownian Motion Boundary Hitting Times (1991) (17)
Accelerating parallel tempering: Quantile tempering algorithm (QuanTA) (2018) (16)
Exact Monte Carlo likelihood-based inference for jump-diffusion processes (2017) (16)
Approximate Predetermined Convergence Properties of the Gibbs Sampler (2001) (15)
Asymptotic analysis of the random walk Metropolis algorithm on ridged densities (2015) (15)
Density Estimation for the Metropolis–Hastings Algorithm (2003) (15)
Multilevel Linear Models, Gibbs Samplers and Multigrid Decompositions (2017) (14)
A comparison theorem for conditioned Markov processes (1991) (14)
On Bayesian analysis of nonlinear continuous‐time autoregression models (2007) (14)
Assessing delivery practices of mothers over time and over space in Uganda, 2003–2012 (2016) (13)
Likelihood‐based inference for correlated diffusions (2007) (13)
Quasi‐stationary Monte Carlo and the ScaLE algorithm (2016) (13)
Continious-time Importance Sampling: Monte Carlo Methods which Avoid Time-discretisation Error (2017) (13)
Regeneration-enriched Markov processes with application to Monte Carlo (2019) (13)
Comment on "Bayesian Computation and Stochastic Systems" (1995) (13)
Methods for Estimating L2 Convergence of Markov Chain-Monte Carlo Techniques (1996) (12)
Enhancing Bayesian risk prediction for epidemics using contact tracing. (2012) (12)
Non-explosivity of limits of conditioned birth and death processes (1997) (11)
Infinite hierarchies and prior distributions (2001) (10)
Inverse method of images (2002) (10)
[Bayesian Computation and Stochastic Systems]: Comment (1995) (10)
An approximation scheme for quasi-stationary distributions of killed diffusions (2018) (10)
Exact sampling of diffusions with a discontinuity in the drift (2015) (10)
Optimal scaling of the random walk Metropolis algorithm under L p mean differentiability (2016) (9)
A utility based approach to information for stochastic differential equations (1993) (9)
One-Shot CFTP; Application to a Class of Truncated Gaussian Densities (2005) (9)
The Acceptance Probability of the Hybrid Monte Carlo Method in High‐Dimensional Problems (2010) (8)
Efficient Real-Time Monitoring of an Emerging Influenza Pandemic: How Feasible? (2020) (8)
Complexity Bounds for MCMC via Diffusion Limits (2014) (8)
Optimal scalings of Metropolis-Hastings algorithms for non-product targets in high dimensions (2009) (8)
Convergence of heavy tailed MCMC algorithms (2001) (8)
Dimension‐free mixing for high‐dimensional Bayesian variable selection (2021) (8)
MEXIT: Maximal un-coupling times for stochastic processes (2017) (8)
Bounds on regeneration times and convergence rates for Markov chainsfn1fn1Work supported in part by NSF Grant DMS 9504561 and EPSRC grant GR/J19900. (1999) (8)
Barker's algorithm for Bayesian inference with intractable likelihoods (2017) (8)
Stability of Partially Implicit Langevin Schemes and Their MCMC Variants (2011) (7)
Football Group Draw Probabilities and Corrections (2022) (7)
Adapting the Gibbs sampler (2018) (7)
Theoretical properties of quasi-stationary Monte Carlo methods (2017) (7)
Markov Chains and De-initialising Processes by (2001) (7)
Optimal Scaling of Metropolis Algorithms on General Target Distributions (2019) (7)
A note on convergence rates of Gibbs sampling for nonparametric mixtures. (1999) (6)
Latent diffusion models for survival analysis (2010) (6)
Analysis of the Gibbs Sampler for Gaussian hierarchical models via multigrid decomposition (2017) (6)
Automatic Zig-Zag sampling in practice (2022) (6)
Bayesian model selection for partially observed diffusion models (2006) (6)
Simulating bridges using confluent diffusions. (2019) (6)
Rao-Blackwellization in the MCMC era (2021) (6)
OPTIMAL SCALING OF METROPOLIS-COUPLED MARKOV CHAIN (2009) (5)
Efficient real-time monitoring of an emerging influenza epidemic: how feasible? (2016) (5)
Existence and stability of relative equilibria in then- body problem (1999) (5)
Speed Up Zig-Zag (2021) (5)
Bayesian Fusion: Scalable unification of distributed statistical analyses (2021) (5)
Optimal scaling of the random walk Metropolis on unimodal elliptically symmetric targets. (2009) (4)
Hitting Time and Convergence Rate Bounds for Symmetric Langevin Diffusions (2016) (4)
Optimal scaling of MCMC beyond Metropolis (2021) (4)
Corrigendum: Perfect slice samplers (2002) (4)
A note on formal constructions of sequential conditional couplings (2013) (4)
A New Method for Coupling Random Fields (2002) (4)
Air Markov Chain Monte Carlo (2018) (4)
Optimal Temperature Spacing for Regionally Weight-preserving Tempering (2018) (4)
Observed diffusion processes (with discussion). (2006) (4)
Rao–Blackwellisation in the Markov Chain Monte Carlo Era (2021) (4)
Tempered Langevin diffusions and algorithms (2002) (4)
Random-weight particle filtering of continuous time (2010) (3)
Possible biases induced by MCMC convergence. (1999) (3)
On the automatic choice of reversible jumps (1998) (3)
Skew brownian motion and complexity of the alps algorithm (2020) (3)
Stereographic Markov Chain Monte Carlo (2022) (3)
Stability of noisy Metropolis – (2015) (3)
An empirical study of the efficiency of EA for diffusion simulation (2008) (3)
Theoretical Properties of Quasistationary Monte Carlo Methods (2017) (3)
Efficient Bernoulli factory MCMC for intractable likelihoods (2020) (3)
Simulation from quasi-stationary distributions on reducible state spaces (2016) (3)
Efficient Bernoulli factory MCMC for intractable posteriors (2020) (3)
A note on the polynomial ergodicity of the one-dimensional Zig-Zag process (2021) (3)
Particle Filtering for Diffusions Avoiding Time-Discretisations (2006) (2)
Divide-and-Conquer Monte Carlo Fusion (2021) (2)
ON THE GEOMETRIC ERGODICITY OF HYBRID SAMPLERSG (2003) (2)
Filtering systems of coupled stochastic differential equations partially observed at high frequency (2007) (2)
Perfect posterior simulation for mixture and hidden Markov models (2010) (2)
MEXIT: Maximal un-coupling times for Markov processes (2017) (2)
Finding Authorities and Hubs FromLink Stru tures on the World Wide (2000) (1)
Irreducible Markov Chain Monte Carlo Schemes for Partially Observed Diffusions (2006) (1)
An ergodicity result for adaptive Langevin algorithms (2009) (1)
Inversion of the method of images. (2002) (1)
Non parametric Bayesian drift estimation for one-dimensional diffusion processes (2009) (1)
Exact Bayesian inference for diffusion driven Cox processes (2020) (1)
Hitting Time and Convergence Rate Bounds for Symmetric Langevin Diffusions (2017) (1)
Annealed Leap-Point Sampler for Multimodal Target Distributions (2021) (1)
Bayesian epidemic risk prediction-knowledge transfer and usability at all levels (2013) (1)
The Computational Cost of Blocking for Sampling Discretely Observed Diffusions (2020) (1)
Recent progress on computable bounds and the simple slice sampler (1999) (1)
Scaling limits for the transient phase. (2005) (1)
Bayesian semi-parametric inference for diffusion processes using splines (2021) (1)
An epidemic model for an evolving pathogen with strain-dependent immunity. (2020) (1)
Obituary: Richard Lewis Tweedie (2002) (1)
Latent diffusion models for event history analysis (2007) (1)
Discussion of 'slice sampling' by Radford M. Neal. (2003) (1)
Rates of convergence for Markov chains associated with Dirichlet processes. (2000) (1)
A Bayesian Decision Theoretic Characterization of Poisson Processes (1991) (1)
Erratum to: Stability of noisy Metropolis–Hastings (2018) (1)
A Study of the Efficiency of Exact Methods for Diffusion Simulation (2012) (1)
Exact Simulation and Bayesian Inference for Jump-Diusion Processes (2010) (1)
Discussion of "Sequential Quasi-Monte-Carlo Sampling" by M. Gerber and N. Chopin (2015) (1)
Whether ’tis Nobler in the Mind to Suffer the Slings and Arrows of Outrageous Mixing Problems, or to Take Arms Against a Sea of Troubles, and by Opposing End Them? (2011) (1)
Contribution to the discussion of \Sequential Quasi-Monte-Carlo Sampling" { Gerber, Chopin (2014) (1)
Rejoinder (1998) (0)
Inference for diffusion models using time change transformations (2011) (0)
An adaptive approach to Langevin MCMC (2011) (0)
IRREDUCIBLEMARKOV CHAINMONTE CARLO SCHEMES FOR PARTIALLY OBSERVEDDIFFUSIONS (2006) (0)
Methods and applications of PDMP samplers with boundary conditions (2023) (0)
Perfect simple slice samplers (2001) (0)
Editorial foreword to special issue on Simulation of Stochastic Networks and related topics (2013) (0)
Electronic Communications in Probability Geometric Ergodicity and Hybrid Markov Chains (1997) (0)
SOME MULTI-STEP COUPLING CONSTRUCTIONS FOR (2000) (0)
We consider the non-explosivity of birth and death processes conditioned not to become extinct. As is often the case with problems involving weak convergence of (1997) (0)
Combinatorial identities associated with CFTP by (2001) (0)
The Boomerang Sampler – Supplement (2020) (0)
Erratum to: Stability of noisy Metropolis–Hastings (2017) (0)
S aling Limits for the Transient Phaseof Lo al Metropolis-Hastings (2003) (0)
A COMPARISON THEOREM FOR CONDITIONED (1991) (0)
A quasi-ergodic theorem for Markov processes. (1999) (0)
Combinatorial identifites associated with CFTP. (2004) (0)
Boundary Hitting Approximations for Markov Processes (1990) (0)
The strong weak convergence of the quasi-EA (2013) (0)
CLTs and Asymptotic Variance of Time-Sampled Markov Chains (2011) (0)
J un 2 01 4 Systematic Physics Constrained Parameter Estimation of Stochastic Di ff erential Equations (2014) (0)
Some boundary hitting problems for diffusion processes (1988) (0)
MCMC methods in high dimension. (2009) (0)
Convergence of Conditional Metropolis-Hastings Samplers , with an Application to Inference for Discretely-Observed Diffusions (2012) (0)
Weight-preserving simulated tempering (2019) (0)
Stability of noisy Metropolis–Hastings (2015) (0)
A note on geometri ergodi ityand oating-point roundo (2000) (0)
Bayesian Inference for Diffusion Processes with Applications in Epidemiology (2008) (0)
Optimal Scaling Results for a Wide Class of Proximal MALA Algorithms (2023) (0)
Retrospective simulation and the Bernoulli factory (2010) (0)
The strong weak convergence of the quasi-EA (2013) (0)
Possible biases induced by MCMC convergence diagnosticsbyMary (1997) (0)
Scaling of Piecewise Deterministic Monte Carlo for Anisotropic Targets (2023) (0)
Polynomial Convergence Rates of Piecewise Deterministic Markov Processes (2023) (0)
Erratum to: Extremal indices, geometric ergodicity of Markov chains, and MCMC (2010) (0)
Markov chain Monte Carlo. A review article for section 10 (probability theory). (2004) (0)
Some stochastic control problems and their applications to inequalities for diffusions (1987) (0)
Monte Carlo simulation of killed diffusions with a single barrier (2006) (0)
Keynote Speakers Gareth Roberts Some Recent Developments in Scaling of Metropolis-hastings Algorithms Eric Moulines Ode Methods for Markov Chain Stability with Applications to Mcmc (joint Work with G. Fort, S. Meyn, P. Priouret) (2006) (0)
Title : The random walk Metropolis : linking theory and practice through a case study Year of publication : 2009 (2009) (0)
Spherical models: Basic states and stability (1981) (0)
Exact Simulation Problems for Jump-Diffusions (2013) (0)
Sampling using Adaptive Regenerative Processes (2022) (0)
The Lifebelt Particle Filter for robust estimation from low-valued count data (2022) (0)
Editorial foreword to special issue on Simulation of Stochastic Networks and related topics (2013) (0)

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What Schools Are Affiliated With Gareth Roberts ?

Gareth Roberts is affiliated with the following schools: