Statistical Methods for Spatio-Temporal Systems: 1st Edition (Hardback) book cover

Statistical Methods for Spatio-Temporal Systems

1st Edition

Edited by Barbel Finkenstadt, Leonhard Held, Valerie Isham

Chapman and Hall/CRC

286 pages | 16 Color Illus. | 122 B/W Illus.

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pub: 2006-10-20
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Description

Statistical Methods for Spatio-Temporal Systems presents current statistical research issues on spatio-temporal data modeling and will promote advances in research and a greater understanding between the mechanistic and the statistical modeling communities.

Contributed by leading researchers in the field, each self-contained chapter starts with an introduction of the topic and progresses to recent research results. Presenting specific examples of epidemic data of bovine tuberculosis, gastroenteric disease, and the U.K. foot-and-mouth outbreak, the first chapter uses stochastic models, such as point process models, to provide the probabilistic backbone that facilitates statistical inference from data. The next chapter discusses the critical issue of modeling random growth objects in diverse biological systems, such as bacteria colonies, tumors, and plant populations. The subsequent chapter examines data transformation tools using examples from ecology and air quality data, followed by a chapter on space-time covariance functions. The contributors then describe stochastic and statistical models that are used to generate simulated rainfall sequences for hydrological use, such as flood risk assessment. The final chapter explores Gaussian Markov random field specifications and Bayesian computational inference via Gibbs sampling and Markov chain Monte Carlo, illustrating the methods with a variety of data examples, such as temperature surfaces, dioxin concentrations, ozone concentrations, and a well-established deterministic dynamical weather model.

Reviews

"… an extremely well-written summary of important topics in the analysis of spatial point processes. … The authors do an excellent job focusing on those theoretical concepts and methods that are most important in applied research. … this is the first text to tackle difficult issues of simulation-based inference … The authors have a very impressive knack for explaining complicated topics very clearly … Its excellent survey of the vast array of models is reason enough to own it. As computer technology and speed advance … the authors' clear, detailed, and comprehensive survey of simulation methods for spatial point processes will become increasingly important."

-Journal of the American Statistical Association

xtremely well-written summary of important topics in the analysis of spatial point processes. … The authors do an excellent job focusing on those theoretical concepts and methods that are most important in applied research. … this is the first text to tackle difficult issues of simulation-based inference … The authors have a very impressive knack for explaining complicated topics very clearly … Its excellent survey of the vast array of models is reason enough to own it. As computer technology and speed advance … the authors' clear, detailed, and comprehensive survey of simulation methods for spatial point processes will become increasingly important."

-Journal of the American Statistical Association

Table of Contents

Preface

Spatio-Temporal Point Processes: Methods and Applications

Peter J. Diggle

Spatio-Temporal Modeling-With a View to Biological Growth

Eva B. Vedel Jensen, Kristjana Ýr Jónsdóttir, Jürgen Schmiegel, and Ole E. Barndorff-Nielsen

Using Transforms to Analyze Space-Time Processes

Montserrat Fuentes, Peter Guttorp, and Paul D. Sampson

Geostatistical Space-Time Models, Stationarity, Separability, and Full Symmetry

Tilmann Gneiting, Marc G. Genton, and Peter Guttorp

Space-Time Modeling of Rainfall for Continuous Simulation

Richard E. Chandler, Valerie Isham, Enrica Bellone, Chi Yang, and Paul Northrop

A Primer on Space-Time Modeling from a Bayesian Perspective

Dave Higdon

Index

About the Series

Chapman & Hall/CRC Monographs on Statistics and Applied Probability

Learn more…

Subject Categories

BISAC Subject Codes/Headings:
MAT029000
MATHEMATICS / Probability & Statistics / General