620 Pages 137 B/W Illustrations
    by CRC Press

    Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. It takes a unified, integrated approach to the material, providing cross-references among chapters.

    The handbook begins with a historical introduction detailing the evolution of the field. It then focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and spatial point patterns. The book also contains a section on space–time work as well as a section on important topics that build upon earlier chapters.

    By collecting the major work in the field in one source, along with including an extensive bibliography, this handbook will assist future research efforts. It deftly balances theory and application, strongly emphasizes modeling, and introduces many real data analysis examples.

    Historical Introduction, Peter J. Diggle

    Continuous Spatial Variation
    Continuous Parameter Stochastic Process Theory, Tilmann Gneiting and Peter Guttorp
    Classical Geostatistical Methods, Dale L. Zimmerman and Michael Stein
    Likelihood-Based Methods, Dale L. Zimmerman
    Spectral Domain, Montserrat Fuentes and Brian Reich
    Asymptotics for Spatial Processes, Michael Stein
    Hierarchical Modeling with Spatial Data, Christopher K. Wikle
    Low Rank Representations for Spatial Processes, Christopher K. Wikle
    Constructions for Nonstationary Spatial Processes, Paul D. Sampson
    Monitoring Network Design, James V. Zidek and Dale L. Zimmerman
    Non-Gaussian and Nonparametric Models for Continuous Spatial Data, Mark F.J. Steel and Montserrat Fuentes

    Discrete Spatial Variation
    Discrete Spatial Variation, Håvard Rue and Leonard Held
    Conditional and Intrinsic Autoregressions, Leonhard Held and Håvard Rue
    Disease Mapping, Lance Waller and Brad Carlin
    Spatial Econometrics, R. Kelley Pace and James LeSage

    Spatial Point Patterns
    Spatial Point Process Theory, Marie-Colette van Lieshout
    Spatial Point Process Models, Valerie Isham
    Nonparametric Methods, Peter J. Diggle
    Parametric Methods, Jesper Møller
    Modeling Strategies, Adrian Baddeley
    Multivariate and Marked Point Processes, Adrian Baddeley
    Point Process Models and Methods in Spatial Epidemiology, Lance Waller

    Spatio-Temporal Processes
    Continuous Parameter Spatio-Temporal Processes, Tilmann Gneiting and Peter Guttorp
    Dynamic Spatial Models Including Spatial Time Series, Dani Gamerman
    Spatio-Temporal Point Processes, Peter J. Diggle and Edith Gabriel
    Modeling Spatial Trajectories, David R. Brillinger
    Data Assimilation, Douglas W. Nychka and Jeffrey L. Anderson

    Additional Topics
    Multivariate Spatial Process Models, Alan E. Gelfand and Sudipto Banerjee
    Misaligned Spatial Data: The Change of Support Problem, Alan E. Gelfand
    Spatial Aggregation and the Ecological Fallacy, Jonathan Wakefield and Hilary Lyons
    Spatial Gradients and Wombling, Sudipto Banerjee



    Alan E. Gelfand, Department of Statistical Science, Duke University, Durham, North Carolina, USA

    Peter J. Diggle, School of Health and Medicine, Lancaster University, UK

    Montserrat Fuentes, Department of Statistics, North Carolina State University, Raleigh, USA

    Peter Guttorp, Department of Statistics, University of Washington, Seattle, USA, and Norwegian Computing Center, Oslo, Norway

    I very strongly recommend this book for anyone working in spatial statistics at any level. The writing styles are all concise, informative, and even somewhat entertaining given the topic constraints. The editors have done a masterful job of organization and chapter authorship selection.
    Technometrics, May 2012

    … a good starting point for entering each subarea of spatial statistics. … it can serve as a textbook at a graduate level for statistics majors … Handbook of Spatial Statistics is well edited and covers a wide range of topics, providing a very useful reference book for spatial statistics.
    —Chae Young Lim, Journal of the American Statistical Association, December 2011

    … each chapter is concisely written to the point of having no extraneous text but without resorting to overly terse discussion. … the layout and content [are] easily accessible for a variety of usage patterns. … the extensive bibliography provides ample direction for extra, more detailed reading. This Handbook is an excellent and clearly written first stop for any questions or queries one may have about spatial statistics. I wish I had owned this book years ago.
    —Scott A. Sisson, Australian & New Zealand Journal of Statistics, December 2011

    This book is certainly bound to become an influential classic in the field of spatial statistics. … reading it surpassed the expectations. It is a comprehensive piece of work that summarizes current state of the developments of the spatial statistics in its multitude. The range of topics covered is impressive … useful and enlightening for a wide scope of readers — from beginners to rather specialized researchers … Readers with an ISCB background will benefit from reading this book in many ways. … this book really sets the standard for modern spatial statistics as a field for years to come. Anybody even mildly interested in the theory or applications of various parts of spatial statistics should read it, or even better, to have it handy as an authoritative and remarkably useful reference.
    ISCB News, No. 51, June 2011

    … the chapters have a very good scientific quality … the reading [is] rather easy and pleasant … the book thoroughly covers the field of spatial statistics and deserves its name of ‘handbook.’ It will be useful to specialists of spatial statistics as a reference book, and also to those who wish to learn the methods used in this field.
    Biometrics, June 2011

    … an exciting handbook, aiming to present a comprehensive treatment of both classical and state-of-the-art topics in the area of spatial statistics. … this book is thoroughly edited and provides comprehensive, coherent, and unified summaries of specific methodological topics from spatial statistics. All the chapters were written by leading researchers in spatial statistics, with a good balance of theory and application through a synthesis of the key methodological developments and examples and case studies using real spatial data. … It is deeply impressive that the handbook covers such a wide range of topics ranging from spatial to spatial–temporal processes. … a valuable handbook for all researchers in spatial statistics, the biostatisticians interested in spatial epidemiology and ecology, and those who need up-to-date guidance in applying modern spatial methods to real data. I enjoyed reading this book very much and I would recommend it …
    Statistics in Medicine, 2011, 30

    As spatial statistics is an important, fast growing field of statistics, it was time to publish a book like this which can be seen as a successor of the famous work by Noel Cressie. The authors are all high-ranked statisticians with great experience in both teaching and research. … The editors are to be credited for their achievement to unite so many methods of spatial statistics in one volume. The reviewer is sure that this will lead to great progress in spatial statistics … the reviewer warmly recommends this great volume to all spatial statisticians. …
    Biometrical Journal, 53 (2011), 1

    … The time has come for a new reference book in spatial statistics. This handbook remarkably achieves this aim. … The editorial quality of the book is absolutely remarkable. … In some chapters, R or WinBugs code is made available. I strongly recommend Handbook of Spatial Statistics as a textbook for an advanced class in spatial statistics and as a reference book for anyone dealing with spatial data. It will definitely be one of my favorite books in the field for years to come, and I am convinced that it will be the case for many scientists. …
    Statistics and Computing, October 2010