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Gaussian Markov random fields: theory and applications

Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational...

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Detalles Bibliográficos
Autores principales: Rue, Havard, Held, Leonhard
Lenguaje:eng
Publicado: Taylor and Francis 2005
Materias:
Acceso en línea:http://cds.cern.ch/record/1989945
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author Rue, Havard
Held, Leonhard
author_facet Rue, Havard
Held, Leonhard
author_sort Rue, Havard
collection CERN
description Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects. This book includes extensive case-studies and, online, a c-library for fast and exact simulation. With chapters contributed by leading researchers in the field, this volume is essential reading for statisticians working in spatial theory and its applications, as well as quantitative researchers in a wide range of science fields where spatial data analysis is important.
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institution Organización Europea para la Investigación Nuclear
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publishDate 2005
publisher Taylor and Francis
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spelling cern-19899452021-04-21T20:31:22Zhttp://cds.cern.ch/record/1989945engRue, HavardHeld, LeonhardGaussian Markov random fields: theory and applicationsMathematical Physics and MathematicsGaussian Markov Random Field (GMRF) models are most widely used in spatial statistics - a very active area of research in which few up-to-date reference works are available. This is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects. This book includes extensive case-studies and, online, a c-library for fast and exact simulation. With chapters contributed by leading researchers in the field, this volume is essential reading for statisticians working in spatial theory and its applications, as well as quantitative researchers in a wide range of science fields where spatial data analysis is important.Taylor and Francisoai:cds.cern.ch:19899452005
spellingShingle Mathematical Physics and Mathematics
Rue, Havard
Held, Leonhard
Gaussian Markov random fields: theory and applications
title Gaussian Markov random fields: theory and applications
title_full Gaussian Markov random fields: theory and applications
title_fullStr Gaussian Markov random fields: theory and applications
title_full_unstemmed Gaussian Markov random fields: theory and applications
title_short Gaussian Markov random fields: theory and applications
title_sort gaussian markov random fields: theory and applications
topic Mathematical Physics and Mathematics
url http://cds.cern.ch/record/1989945
work_keys_str_mv AT ruehavard gaussianmarkovrandomfieldstheoryandapplications
AT heldleonhard gaussianmarkovrandomfieldstheoryandapplications