The Resource Case studies in spatial point process modeling, Adrian Baddeley [and others] (eds.), (electronic resource)

Case studies in spatial point process modeling, Adrian Baddeley [and others] (eds.), (electronic resource)

Label
Case studies in spatial point process modeling
Title
Case studies in spatial point process modeling
Statement of responsibility
Adrian Baddeley [and others] (eds.)
Contributor
Subject
Genre
Language
eng
Summary
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. Adrian Baddeley is Professor of Statistics at the University of Western Australia (Perth, Australia) and a Fellow of the Australian Academy of Science. His main research interests are in stochastic geometry, stereology, spatial statistics, image analysis and statistical software. Pablo Gregori is senior lecturer of Statistics and Probability at the Department of Mathematics, University Jaume I of Castellon. His research fields of interest are spatial statistics, mainly on spatial point processes, and measure theory of functional analysis. Jorge Mateu is Assistant Professor of Statistics and Probability at the Department of Mathematics, University Jaume I of Castellon and a Fellow of the Spanish Statistical Society and of Wessex Institute of Great Britain. His main research interests are in stochastic geometry and spatial statistics, mainly spatial point processes and geostatistics. Radu Stoica obtained his Ph. D. in 2001 from the University of Nice Sophia Anitpolis. He works within the biometry group at INRA Avignon. His research interests are related to the study and the simulation of point processes applied to pattern modeling and recognition. The aimed application domains are image processing, astronomy and environmental sciences. Dietrich Stoyan is Professor of Applied Stochastics at TU Bergakademie Freiberg, Germany. Since the end of the 1970s he has worked in the fields of stochastic geometry and spatial statistics
Member of
Cataloging source
COO
Dewey number
519.2/3
Illustrations
  • illustrations
  • maps
Index
no index present
LC call number
QA274.42
LC item number
.C37 2006
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
Baddeley, Adrian
Series statement
Lecture notes in statistics
Series volume
185
http://library.link/vocab/subjectName
  • Point processes
  • Spatial analysis (Statistics)
  • Processus ponctuels
  • MATHEMATICS
  • Point processes
  • Spatial analysis (Statistics)
  • Point processes
  • Spatial analysis (Statistics)
Label
Case studies in spatial point process modeling, Adrian Baddeley [and others] (eds.), (electronic resource)
Link
http://dx.doi.org/10.1007/0-387-31144-0
Instantiates
Publication
Note
Majority of the contributions in this book represents the reviewed version of the papers presented at a conference on spatial point process modelling and its applications held the week before Easter 2004 in Benicàssim, Castellón, Spain
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Fundamentals of Point Process Statistics, Dietrich Stoyan -- Modelling Spatial Point Patterns in R -- Strong Markov Property of Poisson Processes and Slivnyak Formula -- Bayesian Analysis of Markov Point Processes -- Statistics for Locally Scaled Point Processes -- Nonparametric Testing of Distribution Functions in Germ-grain Models -- Principal Component Analysis for Spatial Point Processes: Assessing the Appropriateness of the Approach in an Ecological Context -- On Modelling of Refractory Castables by Marked Gibbs and Gibbsian-like Processes -- Source Detection in an Outbreak of Legionnaire's Disease -- Doctors' Prescribing Patterns in the Midi-Pyrénées Region of France: Point-process Aggregation -- Strain-typing Transmissible Spongiform Encephalopathies Using Replicated Spatial Data -- Modelling the Bivariate Spatial Distribution of Amacrine Cells -- Analysis of Spatial Point Patterns in Microscopic and Macroscopic Biological Image Data -- Spatial Marked Point Patterns for Herd Dispersion in a Savanna Wildlife Herbivore Community in Kenya -- Diagnostic Analysis of Space-Time Branching Processes for Earthquakes -- Assessing Spatial Point Process Models Using Weighted K-functions: Analysis of California Earthquakes
Dimensions
unknown
Extent
1 online resource (xvii, 306 pages)
Form of item
online
Isbn
9780387283111
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations, maps.
Specific material designation
remote
Stock number
978-0-387-28311-1
System control number
  • (OCoLC)68213735
  • (OCoLC)ocm68213735
Label
Case studies in spatial point process modeling, Adrian Baddeley [and others] (eds.), (electronic resource)
Link
http://dx.doi.org/10.1007/0-387-31144-0
Publication
Note
Majority of the contributions in this book represents the reviewed version of the papers presented at a conference on spatial point process modelling and its applications held the week before Easter 2004 in Benicàssim, Castellón, Spain
Bibliography note
Includes bibliographical references
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
Fundamentals of Point Process Statistics, Dietrich Stoyan -- Modelling Spatial Point Patterns in R -- Strong Markov Property of Poisson Processes and Slivnyak Formula -- Bayesian Analysis of Markov Point Processes -- Statistics for Locally Scaled Point Processes -- Nonparametric Testing of Distribution Functions in Germ-grain Models -- Principal Component Analysis for Spatial Point Processes: Assessing the Appropriateness of the Approach in an Ecological Context -- On Modelling of Refractory Castables by Marked Gibbs and Gibbsian-like Processes -- Source Detection in an Outbreak of Legionnaire's Disease -- Doctors' Prescribing Patterns in the Midi-Pyrénées Region of France: Point-process Aggregation -- Strain-typing Transmissible Spongiform Encephalopathies Using Replicated Spatial Data -- Modelling the Bivariate Spatial Distribution of Amacrine Cells -- Analysis of Spatial Point Patterns in Microscopic and Macroscopic Biological Image Data -- Spatial Marked Point Patterns for Herd Dispersion in a Savanna Wildlife Herbivore Community in Kenya -- Diagnostic Analysis of Space-Time Branching Processes for Earthquakes -- Assessing Spatial Point Process Models Using Weighted K-functions: Analysis of California Earthquakes
Dimensions
unknown
Extent
1 online resource (xvii, 306 pages)
Form of item
online
Isbn
9780387283111
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Other physical details
illustrations, maps.
Specific material designation
remote
Stock number
978-0-387-28311-1
System control number
  • (OCoLC)68213735
  • (OCoLC)ocm68213735

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