D
Dani Gamerman
Researcher at Federal University of Rio de Janeiro
Publications - 79
Citations - 4832
Dani Gamerman is an academic researcher from Federal University of Rio de Janeiro. The author has contributed to research in topics: Markov chain Monte Carlo & Bayesian inference. The author has an hindex of 24, co-authored 76 publications receiving 4576 citations. Previous affiliations of Dani Gamerman include University of Warwick.
Papers
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Book
Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference
TL;DR: Model Adequacy Model Choice: MCMC Over Model and Parameter Spaces Convergence Acceleration Exercises Further topics in MCMC are explained.
Book
Markov Chain Monte Carlo: Stochastic Simulation for Bayesian Inference, Second Edition
Dani Gamerman,Hedibert F. Lopes +1 more
Journal ArticleDOI
Sampling from the posterior distribution in generalized linear mixed models
TL;DR: This paper presents a new methodology for making Bayesian inference about exponential family regression models, overdispersed data and longitudinal studies and involves the use of Markov chain Monte Carlo techniques.
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Bayesian analysis of extreme events with threshold estimation
TL;DR: A mixture model is introduced that combines a parametric form for the center and a GPD for the tail of the distributions and uses all observations for inference about the unknown parameters from both distributions, the threshold included.
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Spatial process modelling for univariate and multivariate dynamic spatial data
TL;DR: The resulting posterior and predictive inference enables summaries in the form of tables and maps, which help to reveal the nature of the spatiotemporal behaviour as well as the associated uncertainty.