Peter Green

Q: What Schools Are Affiliated With Peter Green

Peter Green is affiliated with the following schools: University of Sheffield, University of Bristol, University of Oxford, University of Technology Sydney, Durham University

Peter Green 's AcademicInfluence.com Rankings

Peter Green

Mathematics

#4247

World Rank

#6074

Historical Rank

Statistics

#226

World Rank

#281

Historical Rank

mathematics Degrees

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Mathematics

Peter Green 's Degrees

Masters Mathematics University of Oxford

Why Is Peter Green Influential?

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According to Wikipedia, Peter James Green, FRS is a British Bayesian statistician. He is Emeritus Professor and Professorial Research Fellow at the University of Bristol, and a professor at the University of Technology, Sydney. He is distinguished for his contributions to computational statistics, in particular his contributions to spatial statistics and semi-parametric regression models and also his development of reversible-jump Markov chain Monte Carlo.

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Peter Green '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

Reversible jump Markov chain Monte Carlo computation and Bayesian model determination (1995) (6152)
Markov chain Monte Carlo in Practice (1996) (5121)
Smoothing reference centile curves: the LMS method and penalized likelihood. (1992) (2468)
On Bayesian Analysis of Mixtures with an Unknown Number of Components (with discussion) (1997) (1990)
Bayesian reconstructions from emission tomography data using a modified EM algorithm. (1990) (1316)
Corrigendum: On Bayesian analysis of mixtures with an unknown number of components (1997) (1127)
Bayesian Computation and Stochastic Systems (1995) (1052)
Computing Dirichlet Tessellations in the Plane (1978) (724)
Iteratively reweighted least squares for maximum likelihood estimation (1984) (647)
Spatial Statistics and Bayesian Computation (1993) (539)
On Use of the EM Algorithm for Penalized Likelihood Estimation (1990) (407)
Hidden Markov Models and Disease Mapping (2002) (360)
Trans-dimensional Markov chain Monte Carlo (2000) (348)
Penalized Likelihood for General Semi-Parametric Regression Models. (1987) (322)
Decomposable graphical Gaussian model determination (1999) (292)
Modelling Heterogeneity With and Without the Dirichlet Process (2001) (291)
Delayed rejection in reversible jump Metropolis–Hastings (2001) (286)
Model-based geostatistics. Discussion. Authors' reply (1998) (277)
Highly Structured Stochastic Systems (2003) (258)
Bayesian Model-Based Clustering Procedures (2007) (240)
[Bayesian Computation and Stochastic Systems]: Rejoinder (1995) (226)
Exact Sampling from a Continuous State Space (1998) (198)
Spatial statistics and Bayesian computation (with discussion) (1993) (168)
Bayesian computation: a summary of the current state, and samples backwards and forwards (2015) (162)
Modelling spatially correlated data via mixtures: a Bayesian approach (2002) (129)
Metropolis Methods, Gaussian Proposals and Antithetic Variables (1992) (127)
Reversible jump MCMC (2009) (126)
Discussion on the paper by Spiegelhalter, Best, Carlin and van der Linde (2002) (124)
Discussion of 'Bayesian image restoration with two applications in spatial statistics' by J Besag, J C York & A Mollie (1991) (122)
Semi-Parametric Generalized Linear Models. (1985) (121)
Bayesian alignment using hierarchical models, with applications in protein bioinformatics (2005) (117)
LOGICOIL - multi-state prediction of coiled-coil oligomeric state (2013) (95)
Bayesian Variable Selection and the Swendsen-Wang Algorithm (2004) (77)
Mixture models in measurement error problems, with reference to epidemiological studies (2002) (76)
Constructing the Convex Hull of a Set of Points in the Plane (1979) (71)
BGX: a fully Bayesian integrated approach to the analysis of Affymetrix GeneChip data. (2005) (61)
Bayesian Analysis of Poisson Mixtures (2002) (57)
Sampling decomposable graphs using a Markov chain on junction trees (2011) (55)
Exact sampling for Bayesian inference: towards general purpose algorithms (1998) (53)
Global and local priors, and the location of lesions using gamma-camera imagery (1991) (52)
Boundary detection through dynamic polygons (1998) (51)
SCORER 2.0: an algorithm for distinguishing parallel dimeric and trimeric coiled-coil sequences (2011) (42)
Lead discussion on 'Varying coefficient models' by Hastie & Tibshirani (1993) (41)
Enumerating the Junction Trees of a Decomposable Graph (2009) (36)
Concomitants and correlation estimates (1976) (35)
Bayesian analysis of factorial experiments by mixture modelling (2000) (33)
Bayesian Computation and Stochastic (1995) (31)
The Bernstein–von Mises theorem and nonregular models (2012) (30)
Bayesian Growth Curves Using Normal Mixtures With Nonparametric Weights (2003) (25)
Sensitivity of inferences in forensic genetics to assumptions about founding genes (2009) (25)
Bayesian choice among Markov models of ion channels using Markov chain Monte Carlo (1999) (25)
Probability and Mathematical Genetics: Papers in Honour of Sir John Kingman (2010) (23)
A Graphical Diagnostic for Identifying Influential Model Choices in Bayesian Hierarchical Models (2010) (22)
Penalized Pseudolikelihood Inference in Spatial Interaction Models with Covariates (2000) (22)
Bayesian network management (1998) (22)
Efficient Model Determination for Discrete Graphical Models (2000) (21)
Bayesian computation: a perspective on the current state, and sampling backwards and forwards (2015) (19)
Parallel Chains, Delayed Rejection and Reversible Jump MCMC for Object Recognition (2000) (18)
Enumerating the decomposable neighbors of a decomposable graph under a simple perturbation scheme (2009) (17)
Alignment of Multiple Configurations Using Hierarchical Models (2009) (17)
Consistency of Deviance‐Based M Estimators (1987) (16)
COVID-19 and the difficulty of inferring epidemiological parameters from clinical data (2020) (15)
Markov chain Monte Carlo in image analysis (1996) (15)
Modelling data from single photon emission computed tomography (1994) (14)
Paternity testing and other inference about relationships from DNA mixtures. (2016) (13)
Bayesian refinement of protein functional site matching (2007) (11)
Structure and uncertainty: Graphical models for understanding complex data (2005) (9)
MAD‐Bayes matching and alignment for labelled and unlabelled configurations (2015) (9)
On the "Poisson Trick" and its Extensions for Fitting Multinomial Regression Models (2017) (9)
Discussion of 'Bayesian backfitting' by Hastie and Tibshirani (2000) (9)
Inference from genome‐wide association studies using a novel Markov model (2008) (8)
Colouring and breaking sticks: random distributions and heterogeneous clustering (2010) (8)
Stochastic Models, Statistical Methods & Algorithms in Image Analysis (1991) (7)
Inference about complex relationships using peak height data from DNA mixtures (2020) (6)
Model Choice using Reversible Jump Markov Chain (2011) (6)
Spatially Correlated Allocation Models for Count Data (2000) (6)
Object Restoration Through Dynamic Polygons (1995) (5)
Casework applications of probabilistic genotyping methods for DNA mixtures that allow relationships between contributors. (2020) (5)
A structural Markov property for decomposable graph laws that allows control of clique intersections (2017) (5)
The Oxford Handbook of Applied Bayesian Analysis (2010) (4)
Contribution to discussion of paper by U Grenander & MI Miller (1994) (4)
Discussion on the paper by Brooks, Giudici and Roberts (2003) (4)
Trans-dimensional Markov chain Monte Carlo (Chapter 6) (2003) (3)
Introduction to Finite Mixtures (2017) (3)
GAUSSIAN PROCESSES FOR REGRESSION AND CLASSIFICATION TASKS USING NON-GAUSSIAN LIKELIHOODS (2019) (3)
The Bernstein-von Mises theorem for non-regular generalised linear inverse problems (2012) (2)
A Bayesian hierarchical model for photometric red shifts (2008) (2)
COMPSTAT 1998, Proceedings in Computational Statistics 13th Symposium held in Bristol, Great Britain, 1998 (1998) (2)
Discussion of ‘Beyond mean regression’ (2013) (2)
Notes on the life and work of R. A. Fisher (2003) (2)
Discussion of 'Beyond Mean Regression' by Thomas Kneib (2013) (2)
Bayesian protein sequence and structure alignment (2014) (2)
Conjugate generalized linear mixed models for clustered data (2017) (2)
In the proceedings of the 14th International Workshop on Statistical Modelling, Graz (Austria) July (1999) (1)
A Bayesian Hierarchical Model for Photometric Redshifts (2007) (1)
Applications of the Local critique plot (2010) (1)
Conditioning a branching process on non-extinction (1977) (1)
Using gaussian mixtures with unknownnumber of components for mixed (1999) (1)
Grappa: R functions for probability propagation (2005) (1)
A weaker structural Markov property for decomposable graph laws (2017) (1)
The official bulletin of the International Society for Bayesian Analysis (2004) (0)
Submitted to the Annals of Statistics THE BERNSTEIN – VON MISES THEOREM FOR NON-REGULAR GENERALISED LINEAR INVERSE PROBLEMS (2012) (0)
Towards a Fast Bayesian Climate Reconstruction (2016) (0)
M E ] 3 A pr 2 01 8 Bayesian Protein Sequence and Structure Alignment (2018) (0)
COMPSTAT - Procs in Computational Statistics (1998) (0)
Consistency and efficiency of Bayesian estimators in generalised linear inverse problems (2011) (0)
(2018). A structural Markov property for decomposable graph laws that allows control of clique intersections. Biometrika 105 (1), 19-29. (2018) (0)
Bayesian modelling for matching and alignment of biomolecules (2018) (0)
Markov chain Monte Carlo in action a tutorial (1999) (0)
Discussion of paper by Cowell, Graversen, Lauritzen and Mortera (2015) (0)
Analysis of grouped data using conjugate generalized linear mixed models (2019) (0)
Stochastic Algorithms and Bayesian Inference (1992) (0)
Bayesian inference for poisson mixtures and its application to disease mapping (2001) (0)
Editorial (1994) (0)
Small distances, and Monte Carlo testing of spatial pattern (1978) (0)
Free energy biased sampling and mixture modelling (2010) (0)
Discussion (2001) (0)
Bayesian computation: a summary of the current state, and samples backwards and forwards (2015) (0)
Conference on Conditional Independence Structures and Extremes (2016) (0)

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What Schools Are Affiliated With Peter Green ?

Peter Green is affiliated with the following schools:

Peter Green 's Academic­Influence.com Rankings