Gelfand / Diggle / Guttorp Handbook of Spatial Statistics

1. Auflage 2010
ISBN: 978-1-4200-7288-4
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 619 Seiten

Reihe: Chapman & Hall/CRC Handbooks of Modern Statistical Methods

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.

Zielgruppe

Graduate students, researchers, and practitioners in statistics; quantitative researchers in epidemiology, biology, geography, engineering, and social sciences.

Autoren/Hrsg.

Gelfand, Alan E.

Diggle, Peter

Guttorp, Peter

Fuentes, Montserrat

Fachgebiete

• Mathematik | Informatik Mathematik Stochastik Mathematische Statistik
• Mathematik | Informatik Mathematik Stochastik Wahrscheinlichkeitsrechnung

Inhaltsverzeichnis

Introduction
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

Index

Über Autor(innen)

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