Hierarchical Modeling and Analysis for Spatial Data, Second Edition

✍ Scribed by Banerjee, Sudipto; Carlin, Bradley P.; Gelfand, Alan E

Publisher: CRC Press
Year: 2015
Tongue: English
Leaves: 583
Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability
Edition: 2ed.
Category: Library

No coin nor oath required. For personal study only.

✦ Synopsis

""This is a very welcome second edition of a nice and very successful book written by three experts in the field ... I have no doubts that this updated text will continue being a compulsory reference for those graduate students and researchers interested in understanding and applying any of the three areas of spatial statistics ... printed in color and this helps to see better some of the graphical representations Read more...

Abstract: ""This is a very welcome second edition of a nice and very successful book written by three experts in the field ... I have no doubts that this updated text will continue being a compulsory reference for those graduate students and researchers interested in understanding and applying any of the three areas of spatial statistics ... printed in color and this helps to see better some of the graphical representations ... excellent book that I highly recommend for anyone interested in the fascinating field of space and space-time modeling. This is definitely one of those second edition books that is wor

✦ Table of Contents

Content: Front Cover
Dedication
Contents
Preface to the Second Edition
Preface to the First Edition
Chapter 1 --
Overview of spatial data problems
Chapter 2 --
Basics of point-referenced data models
Chapter 3 --
Some theory for point-referenced data models
Chapter 4 --
Basics of areal data models
Chapter 5 --
Basics of Bayesian inference
Chapter 6 --
Hierarchical modeling for univariate spatial data
Chapter 7 --
Spatial misalignment
Chapter 8 --
Modeling and Analysis for Point Patterns
Chapter 9 --
Multivariate spatial modeling for point-referenced data. Chapter 10 --
Models for multivariate areal dataChapter 11 --
Spatiotemporal modeling
Chapter 12 --
Modeling large spatial and spatiotemporal datasets
Chapter 13 --
Spatial gradients and wombling
Chapter 14 --
Spatial survival models
Chapter 15 --
Special topics in spatial process modeling
Appendices
Appendix A --
Spatial computing methods
Appendix B --
Answers to selected exercises
Bibliography
Back Cover.

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