Håvard Rue

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	Tutte	Dal 2019
Citazioni	30732	18217
Indice H	64	49
i10-index	179	134

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54 articoli

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Finn LindgrenUniversity of EdinburghEmail verificata su ed.ac.uk
Daniel SimpsonNormal ComputingEmail verificata su normalcomputing.ai
Leonhard HeldProfessor of Biostatistics, University of ZurichEmail verificata su uzh.ch
Sara MartinoNorwegian University of Science and TechnologyEmail verificata su ntnu.no
Sigrunn Holbek SørbyeUiT The Arctic University of NorwayEmail verificata su uit.no
Andrea RieblerDepartment of Mathematical Sciences, NTNU, Trondheim, NorwayEmail verificata su math.ntnu.no
Elias Teixeira KrainskiKAUSTEmail verificata su kaust.edu.sa
Janine B IllianUniversity of Glasgow, UKEmail verificata su glasgow.ac.uk
Dag MyrhaugDepartment of Marine Technology, Norwegian University of Science and Technology (NTNU)Email verificata su ntnu.no
Haakon BakkaPostDoc, University of OsloEmail verificata su math.uio.no
Janet Van NiekerkKAUSTEmail verificata su kaust.edu.sa
Virgilio Gómez-RubioProfessor, Universidad de Castilla-La ManchaEmail verificata su uclm.es
Nicolas ChopinProfessor of Statistics, ENSAE (Institut Polytechnique de Paris)Email verificata su ensae.fr
Geir-Arne FuglstadNorwegian University of Science and TechnologyEmail verificata su ntnu.no
David BolinKing Abdullah University of Science and TechnologyEmail verificata su kaust.edu.sa
Michela CamelettiUniversità degli studi di BergamoEmail verificata su unibg.it
massimo ventrucciUniversity of BolognaEmail verificata su unibo.it
Roger BivandNorwegian School of EconomicsEmail verificata su nhh.no
Arnoldo FrigessiUniversity of OsloEmail verificata su medisin.uio.no
Daniela Castro-CamiloUniversity of GlasgowEmail verificata su glasgow.ac.uk

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Håvard Rue

King Abdullah University of Science and Technology

Email verificata su kaust.edu.sa - Home page

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Titolo Ordina per citazioni Ordina per anno Ordina per titolo	Citata da Citata da	Anno
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	5896	2009
Gaussian Markov random fields: theory and applications H Rue, L Held Chapman and Hall/CRC, 2005	3654	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	3017	2011
Bayesian spatial modelling with R-INLA F Lindgren, H Rue Journal of statistical software 63 (19), 2015	1284	2015
Penalising model component complexity: A principled, practical approach to constructing priors D Simpson, H Rue, A Riebler, TG Martins, SH Sørbye	1189	2017
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 (1), 395-421, 2017	768	2017
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	717	2013
Bayesian computing with INLA: new features TG Martins, D Simpson, F Lindgren, H Rue Computational Statistics & Data Analysis 67, 68-83, 2013	682	2013
Fast sampling of Gaussian Markov random fields H Rue Journal of the Royal Statistical Society: Series B (Statistical Methodology …, 2001	558	2001
An intuitive Bayesian spatial model for disease mapping that accounts for scaling A Riebler, SH Sørbye, D Simpson, H Rue Statistical methods in medical research 25 (4), 1145-1165, 2016	459	2016
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, 109-131, 2013	435	2013
Constructing priors that penalize the complexity of Gaussian random fields GA Fuglstad, D Simpson, F Lindgren, H Rue Journal of the American Statistical Association 114 (525), 445-452, 2019	417	2019
Spatial modeling with R‐INLA: A review H Bakka, H Rue, GA Fuglstad, A Riebler, D Bolin, J Illian, E Krainski, ... Wiley Interdisciplinary Reviews: Computational Statistics 10 (6), e1443, 2018	383	2018
Bayesian inference for generalized linear mixed models Y Fong, H Rue, J Wakefield Biostatistics 11 (3), 397-412, 2010	363	2010
Focus on Sport: Prediction and Retrospective Analysis of Soccer Matches in a League H Rue, Ø Salvesen Journal of the Royal Statistical Society Series D: The Statistician 49 (3 …, 2000	363	2000
Fitting Gaussian Markov random fields to Gaussian fields H Rue, H Tjelmeland Scandinavian journal of Statistics 29 (1), 31-49, 2002	345	2002
Advanced spatial modeling with stochastic partial differential equations using R and INLA E Krainski, V Gómez-Rubio, H Bakka, A Lenzi, D Castro-Camilo, ... Chapman and Hall/CRC, 2018	334	2018
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	312	2007
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	292	2002
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	280	2016

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