1. Introduction -- 2. Theory of Gaussian Markov random fields -- 3. Intrinsic Gaussian Markov random fields -- 4. Case studies in hierarchical modeling -- 5. Approximation techniques -- App. A. Common distributions -- App. B. The library GMRFLib
Summary
Gaussian Markov Random Field (GMRF) models are most widely used in spatial statistics ñ 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 i
Bibliography
Includes bibliographical references
Notes
Online resource; title from PDF title page (Taylor & Francis, viewed October 16, 2017)
