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Case Studies in Spatial Point Process Modeling
. Ed(S): Baddeley, Adrian; Gregori, Pablo; Mateu, Jorge; Stoica, Radu; Stoyan, Dietrich
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Description for Case Studies in Spatial Point Process Modeling
Paperback. Spatial point processes are complex stochastic models that describe the locations of "interesting" events, and (possibly) some information about each event. This book is focused on case studies, rather than methodological aspects of point process modelling. Editor(s): Baddeley, Adrian; Gregori, Pablo; Mateu, Jorge; Stoica, Radu; Stoyan, Dietrich. Series: Lecture Notes in Statistics. Num Pages: 328 pages, biography. BIC Classification: PBWL. Category: (P) Professional & Vocational; (UP) Postgraduate, Research & Scholarly; (UU) Undergraduate. Dimension: 233 x 155 x 17. Weight in Grams: 473.
Point process statistics is successfully used in fields such as material science, human epidemiology, social sciences, animal epidemiology, biology, and seismology. Its further application depends greatly on good software and instructive case studies that show the way to successful work. This book satisfies this need by a presentation of the spatstat package and many statistical examples.
Researchers, spatial statisticians and scientists from biology, geosciences, materials sciences and other fields will use this book as a helpful guide to the application of point process statistics. No other book presents so many well-founded point process case studies.
From the reviews:
"For those ... Read more
Show LessProduct Details
Format
Paperback
Publication date
2005
Publisher
Springer-Verlag New York Inc. United States
Number of pages
328
Condition
New
Series
Lecture Notes in Statistics
Number of Pages
310
Place of Publication
New York, NY, United States
ISBN
9780387283111
SKU
V9780387283111
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
Reviews for Case Studies in Spatial Point Process Modeling
"For those interested in analyzing their spatial data, the wide variatey of examples and approaches here give a good idea of the possibilities and suggest reasonable paths to explore." Michael Sherman for the Journal of the American Statistical Association, December 2006