Havard Rue, Leonhard Held

Gaussian Markov Random Fields

Theory and Applications

• Gebundenes Buch

Produktbeschreibung

There are a wide range of applications for Gaussian Markov Random Fields (GMRFs), from structural time-series analysis to the analysis of longitudinal and survival data, spatio-temporal models, graphical models, and semi-parametric statistics. This book provides various case studies that illustrate the use of GMRFs in complex hierarchical models.

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Gaussian Markov Random Field (GMRF) models, most widely used in spatial statistics are presented in this, the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects.

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Produktdetails

• Verlag: Chapman and Hall/CRC
• Seitenzahl: 280
• Erscheinungstermin: 18. Februar 2005
• Englisch
• Abmessung: 235mm x 157mm x 20mm
• Gewicht: 560g
• ISBN-13: 9781584884323
• ISBN-10: 1584884320
• Artikelnr.: 21309778

Autorenporträt

Havard Rue, Leonhard Held

Inhaltsangabe

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. Gaussian Markov Random Field: Theory and
Applications is the first book on the subject that provides a unified
framework of GMRFs with particular emphasis on the computational aspects.
The 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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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. Gaussian Markov Random Field: Theory and Applications is the first book on the subject that provides a unified framework of GMRFs with particular emphasis on the computational aspects. The 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.

Rezensionen

"I thus enjoyed reading this book and I would recommend it to anyone involved in spatial modelling as a time-effective introduction to the field, including a concern for practical implementation that may be lacking elsewhere and a good stylistic balance between background and technicalities, between bases and illustrations that make it a rather easy reading."

- Christian P. Robert, Université Paris, in Statistics in Medicine, 2006, Vol. 25