Håvard Rue
Håvard Rue
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Geciteerd door
Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations
H Rue, S Martino, N Chopin
Journal of the royal statistical society: Series b (statistical methodology …, 2009
Gaussian Markov random fields: theory and applications
H Rue, L Held
CRC press, 2005
An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach
F Lindgren, H Rue, J Lindström
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2011
Bayesian spatial modelling with R-INLA
F Lindgren, H Rue
Journal of Statistical Software 63 (19), 1-25, 2015
Penalising model component complexity: A principled, practical approach to constructing priors
D Simpson, H Rue, A Riebler, TG Martins, SH Sørbye
Statistical science, 1-28, 2017
Fast sampling of Gaussian Markov random fields
H Rue
Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2001
Bayesian computing with INLA: new features
TG Martins, D Simpson, F Lindgren, H Rue
Computational Statistics & Data Analysis 67, 68-83, 2013
Spatial and spatio-temporal models with R-INLA
M Blangiardo, M Cameletti, G Baio, H Rue
Spatial and spatio-temporal epidemiology 4, 33-49, 2013
Fitting Gaussian Markov random fields to Gaussian fields
H Rue, H Tjelmeland
Scandinavian journal of Statistics 29 (1), 31-49, 2002
Spatio-temporal modeling of particulate matter concentration through the SPDE approach
M Cameletti, F Lindgren, D Simpson, H Rue
AStA Advances in Statistical Analysis 97 (2), 109-131, 2013
Bayesian computing with INLA: a review
H Rue, A Riebler, SH Sørbye, JB Illian, DP Simpson, FK Lindgren
Annual Review of Statistics and Its Application 4, 395-421, 2017
Prediction and retrospective analysis of soccer matches in a league
H Rue, O Salvesen
Journal of the Royal Statistical Society: Series D (The Statistician) 49 (3 …, 2000
Bayesian inference for generalized linear mixed models
Y Fong, H Rue, J Wakefield
Biostatistics 11 (3), 397-412, 2010
On block updating in Markov random field models for disease mapping
L Knorr‐Held, H Rue
Scandinavian Journal of Statistics 29 (4), 597-614, 2002
Approximate Bayesian inference for hierarchical Gaussian Markov random field models
H Rue, S Martino
Journal of statistical planning and inference 137 (10), 3177-3192, 2007
A dynamic mixture model for unsupervised tail estimation without threshold selection
A Frigessi, O Haug, H Rue
Extremes 5 (3), 219-235, 2002
Towards joint disease mapping
L Held, I Natário, SE Fenton, H Rue, N Becker
Statistical methods in medical research 14 (1), 61-82, 2005
Going off grid: Computationally efficient inference for log-Gaussian Cox processes
D Simpson, JB Illian, F Lindgren, SH Sørbye, H Rue
Biometrika 103 (1), 49-70, 2016
A toolbox for fitting complex spatial point process models using integrated nested Laplace approximation (INLA)
JB Illian, SH Sørbye, H Rue
The Annals of Applied Statistics, 1499-1530, 2012
Posterior and cross-validatory predictive checks: a comparison of MCMC and INLA
L Held, B Schrödle, H Rue
Statistical modelling and regression structures, 91-110, 2010
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