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My work has been highlighted by the University of Bristol:  1 |  2 |  3 , and is indexed by Google Scholar. I have been "highly-cited" and in about 2005 was interviewed by the ISI highly-cited team about one of my papers.

Published since 2013

• Healthcare serial killer or coincidence? Statistical issues in investigation of suspected medical misconduct, by the RSS Statistics and the Law section, working group chaired by Peter J. Green (2022) (pdf). Also Summary version. Errata.
• Inference about complex relationships using peak height data from DNA mixtures, by Peter J. Green and Julia Mortera (published online 7 July 2021, open access); also on arXiv. Applied Statistics, 70, 1049-1082 (2021). Associated R package and User guide: KinMix.
• Casework applications of probabilistic genotyping methods for DNA mixtures that allow relationships between contributors, by Peter J. Green, Julia Mortera and Lourdes Prieto (2021), Forensic Science International: Genetics, vol 52, paper 102482; also on arXiv.
• COVID-19 and the difficulty of inferring epidemiological parameters from clinical data, by Simon N. Wood , Ernst C. Wit, Matteo Fasiolo and Peter J. Green (2020). Published in The Lancet: Infectious Diseases, 28 May 2020. Supplementary material. https://arxiv.org/abs/2004.14482 includes also longer original version.
• Analysis of grouped data using conjugate generalized linear mixed models, by Jarod Y.L. Lee, Peter J. Green, Louise M. Ryan (2020) (pdf). Biometrika, 107, 231-237. https://doi.org/10.1093/biomet/asz053. On ArXiv: https://arxiv.org/abs/1709.06288.
• Bayesian protein sequence and structure alignment, by Christopher J. Fallaize, Peter J. Green, Kanti V. Mardia and Stuart Barber. Journal of the Royal Statistical Society (C), 69, 301-325 (2020). ArXiv: http://arxiv.org/abs/1404.1556. https://doi.org/10.1111/rssc.12394
• Introduction to finite mixtures, by Peter J. Green (2017). On ArXiv: http://arxiv.org/abs/1705.01505. Introductory chapter in the Handbook of Mixture Analysis (2019).
• Julian Ernst Besag, 26 March 1945 — 6 August 2010, a biographical memoir, by Peter J. Diggle, Peter J. Green and Bernard W. Silverman. https://doi.org/10.1098/rsbm.2017.0039. On arXiv: https://arxiv.org/abs/1711.10262.
• A structural Markov property for decomposable graph laws that allows control of clique intersections, by Peter J. Green and Alun Thomas (updated October 2017) . Open access in Biometrika, 105, 19-29 (2018). On arXiv: http://arxiv.org/abs/1705.00554.
• Paternity testing and other inference about relationships from DNA mixtures, by Peter J. Green and Julia Mortera (revised January 2017) (pdf). Forensic Science International: Genetics. http://dx.doi.org/10.1016/j.fsigen.2017.02.001. On arXiv: http://arxiv.org/abs/1609.09638.
• MAD-Bayes matching and alignment for labelled and unlabelled configurations, by Peter J. Green (2015). In Geometry driven statistics, edited by Ian L. Dryden and John T. Kent, chapter 19, pp 377-390. Wiley, Chichester.
• The Bernstein-von Mises theorem and non-regular models, by Natalia Bochkina and Peter J. Green (2014) (pdf). Annals of Statistics, 42, 1850-1878. DOI: 10.1214/14-AOS1239. Also on arXiv: http://arxiv.org/abs/1211.3434
• Sampling decomposable graphs using a Markov chain on junction trees, by Peter J. Green and Alun Thomas (2013) (pdf). Biometrika, 100 (1): 91-110; doi: 10.1093/biomet/ass052. On arXiv: http://arxiv.org/abs/1104.4079.

Recently completed reports and papers - not yet published

• On the "Poisson Trick" and its Extensions for Fitting Multinomial Regression Models, by Jarod Y.L. Lee, Peter J. Green, Louise M. Ryan (2017) (pdf). On ArXiv: http://arxiv.org/abs/1707.08538.
• Consistency and efficiency of Bayesian estimators in generalised linear inverse problems, by Natalia Bochkina and Peter J. Green (2012). On ArXiv: http://arxiv.org/abs/1110.3015.