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Statistical Analysis of Spatial and Spatio-Temporal Point Patterns

Peter J. Diggle
€100.99
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A01=Peter J. Diggle
advanced spatial data analysis
Author_Peter J. Diggle
Category=PBT
Category=PSA
complete
Conditional Intensity
cox
Cox Process
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FMD.
homogeneous
Homogeneous Poisson Process
inhomogeneous
Inhomogeneous Poisson Process
interaction
Japanese Black Pine
likelihood-based modeling
Log Gaussian Cox Process
Markov Point Processes
mechanistic spatial models
Monte Carlo Tests
nonparametric spatial methods
Pair Correlation Function
pairwise
Pairwise Interaction Point Process
Pairwise Interaction Process
Point Process
poisson
Poisson Cluster Process
Poisson Process
process
processes
Quadrat Count
R packages for analyzing spatial point process data
R statistical computing
Random Labelling
randomness
Redwood Seedling
Simulation Envelopes
spatial data in the life sciences
spatial epidemiology
spatial point patterns
spatial point process modeling in life sciences
Spatial Point Processes
spatial statistics
spatially referenced point process data
Spatio Temporal Point
Spatio Temporal Point Patterns
Spatio Temporal Point Process
spatio-temporal processes
spatio-temporally indexed data
statistical tools for modeling and analyzing spatial data
Vice Versa

Product details

  • ISBN 9781466560239
  • Weight: 566g
  • Dimensions: 156 x 234mm
  • Publication Date: 23 Jul 2013
  • Publisher: Taylor & Francis Inc
  • Publication City/Country: US
  • Product Form: Hardback
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Description

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.
About Peter J. Diggle

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.

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