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Generalized linear mixed models provide a unified framework for treatment of exponential family regression models, overdispersed data and longitudinal studies. These problems typically involve the… Continue Reading
The aim of this paper is to analyse extremal events using generalized Pareto distributions (GPD), considering explicitly the uncertainty about the threshold. Current practice empirically determines… Continue Reading
Stochastic simulation Bayesian inference approximate methods of inference Markov chains Gibbs sampling Metropolis-Hastings algorithms further topics in MCMC.
Dynamic models are proposed for the study of survival data with explanatory variables whose effects change through time. The parameters modelling these effects are allowed to vary between time… Continue Reading
SUMMARY This paper presents a new methodological approach for carrying out Bayesian inference about dynamic models for exponential family observations. The approach is simulationbased and involves… Continue Reading
There is a considerable literature in spatiotemporal modelling. The approach adopted here applies to the setting where space is viewed as continuous but time is taken to be discrete. We view the data… Continue Reading
An adjustable lock nut comprising a one-piece annular body having an internally threaded axial bore extending between and faces of the body and a circumferential outer face. The body has a narrow… Continue Reading
In many survival studies, covariates effects are time-varying and there is presence of spatial effects. Dynamic models can be used to cope with the variations of the effects and spatial components… Continue Reading