Spatial and spatio-temporal bayesian models with R - INLA

Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4...

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Detalles Bibliográficos
Autores principales: Blangiardo, Marta, Cameletti, Michela
Lenguaje:eng
Publicado: Wiley 2015
Materias:
Mathematical Physics and Mathematics
Acceso en línea:http://cds.cern.ch/record/2020300
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author Blangiardo, Marta
Cameletti, Michela
author_facet Blangiardo, Marta
Cameletti, Michela
author_sort Blangiardo, Marta
collection CERN
description Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior Distr
id cern-2020300
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2015
publisher Wiley
record_format invenio
spelling cern-20203002021-04-21T20:17:23Zhttp://cds.cern.ch/record/2020300engBlangiardo, MartaCameletti, MichelaSpatial and spatio-temporal bayesian models with R - INLAMathematical Physics and Mathematics Dedication iiiPreface ix1 Introduction 11.1 Why spatial and spatio-temporal statistics? 11.2 Why do we use Bayesian methods for modelling spatial and spatio-temporal structures? 21.3 Why INLA? 31.4 Datasets 32 Introduction to 212.1 The language 212.2 objects 222.3 Data and session management 342.4 Packages 352.5 Programming in 362.6 Basic statistical analysis with 393 Introduction to Bayesian Methods 533.1 Bayesian Philosophy 533.2 Basic Probability Elements 573.3 Bayes Theorem 623.4 Prior and Posterior Distributions 643.5 Working with the Posterior Distribution 663.6 Choosing the Prior DistrWileyoai:cds.cern.ch:20203002015
spellingShingle Mathematical Physics and Mathematics
Blangiardo, Marta
Cameletti, Michela
Spatial and spatio-temporal bayesian models with R - INLA
title Spatial and spatio-temporal bayesian models with R - INLA
title_full Spatial and spatio-temporal bayesian models with R - INLA
title_fullStr Spatial and spatio-temporal bayesian models with R - INLA
title_full_unstemmed Spatial and spatio-temporal bayesian models with R - INLA
title_short Spatial and spatio-temporal bayesian models with R - INLA
title_sort spatial and spatio-temporal bayesian models with r - inla
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/2020300
work_keys_str_mv AT blangiardomarta spatialandspatiotemporalbayesianmodelswithrinla
AT camelettimichela spatialandspatiotemporalbayesianmodelswithrinla

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