Description
Statistical Analysis of Spatial and Spatio-Temporal Point Patterns (3rd Ed.)
Chapman & Hall/CRC Monographs on Statistics and Applied Probability Series
Author: Diggle Peter J.
Language: EnglishSubjects for Statistical Analysis of Spatial and Spatio-Temporal...:
Keywords
Inhomogeneous Poisson Process; Spatio Temporal Point Patterns; statistical tools for modeling and analyzing spatial data; FMD; spatio-temporal processes; Pairwise Interaction Point Process; spatial statistics; Log Gaussian Cox Process; spatial point patterns; Spatio Temporal Point Process; spatially referenced point process data; Markov Point Processes; spatio-temporally indexed data; Spatial Point Processes; spatial data in the life sciences; Cox Process; R packages for analyzing spatial point process data; Homogeneous Poisson Process; Poisson Cluster Process; Vice Versa; Monte Carlo Tests; Pairwise Interaction Process; Quadrat Count; Simulation Envelopes; Pair Correlation Function; Point Process; Poisson Process; Spatio Temporal Point; Redwood Seedling; Conditional Intensity; Japanese Black Pine; Random Labelling
Publication date: 01-2023
· 15.6x23.4 cm · Paperback
Publication date: 08-2013
266 p. · 15.6x23.4 cm · Hardback
Description
/li>Contents
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/li>Biography
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Written by a prominent statistician and author, the first edition of this bestseller broke new ground in the then emerging subject of spatial statistics with its coverage of spatial point patterns. Retaining all the material from the second edition and adding substantial new material, Statistical Analysis of Spatial and Spatio-Temporal Point Patterns, Third Edition presents models and statistical methods for analyzing spatially referenced point process data.
Reflected in the title, this third edition now covers spatio-temporal point patterns. It explores the methodological developments from the last decade along with diverse applications that use spatio-temporally indexed data. Practical examples illustrate how the methods are applied to analyze spatial data in the life sciences.
This edition also incorporates the use of R through several packages dedicated to the analysis of spatial point process data. Sample R code and data sets are available on the author?s website.
Introduction. Preliminary Testing. Methods for Sparsely Sampled Patterns. Spatial Point Processes. Nonparametric Methods. Models. Model-Fitting Using Summary Descriptions. Model-Fitting Using Likelihood-Based Methods. Point Process Methods in Spatial Epidemiology. Spatio-Temporal Point Processes. Exploratory Analysis. Empirical Models and Methods. Mechanistic Models and Methods. References.
Peter Diggle is a Distinguished University Professor and group leader of CHICAS at Lancaster University. Dr. Diggle is also an adjunct professor of biostatistics at both Johns Hopkins University’s and Yale University’s Schools of Public Health, adjunct senior researcher in the International Research Institute for Climate and Society at Columbia University, professor of epidemiology and statistics at the University of Liverpool, a trustee for Biometrika, founding co-editor and advisory board member for Biostatistics, and chair of the Strategic Skills Fellowships Panel of the Medical Research Council. His research focuses on the development and application of statistical methods to the biomedical and health sciences.