23 citations · 43 across the 8 of their papers we have counts for
9 papers
Conjugate generalized linear mixed models for clustered data
Jarod Y. L. Lee, Peter J. Green, Louise M. Ryan
This article concerns a class of generalized linear mixed models for clustered data, where the random effects are mapped uniquely onto the grouping structure and are independent be…
On the "Poisson Trick" and its Extensions for Fitting Multinomial Regression Models
Jarod Y. L. Lee, Peter J. Green, Louise M. Ryan
This article is concerned with the fitting of multinomial regression models using the so-called "Poisson Trick". The work is motivated by Chen & Kuo (2001) and Malchow-Møller & Sva…
Introduction to finite mixtures
Peter J. Green
Mixture models have been around for over 150 years, as an intuitively simple and practical tool for enriching the collection of probability distributions available for modelling da…
Bayesian computation: a perspective on the current state, and sampling backwards and forwards
Peter J. Green, Krzysztof Łatuszyński, Marcelo Pereyra +1
The past decades have seen enormous improvements in computational inference based on statistical models, with continual enhancement in a wide range of computational tools, in compe…
Bayesian Protein Sequence and Structure Alignment
Christopher Fallaize, Peter Green, Kanti Mardia +1
The structure of a protein is crucial in determining its functionality, and is much more conserved than sequence during evolution. A key task in structural biology is to compare pr…
The Bernstein-von Mises theorem and nonregular models
Natalia A. Bochkina, Peter J. Green
We study the asymptotic behaviour of the posterior distribution in a broad class of statistical models where the "true" solution occurs on the boundary of the parameter space. We s…