Spatial Statistics and Computational Methods

Jesper Møller

ISBN 10: 0387001360 / ISBN 13: 9780387001364

Verlag: Springer New York, Springer US Mär 2003, 2003

Beschreibung

Neuware -Spatial statistics and Markov Chain Monte Carlo (MCMC) techniques haveeach undergone major developments in the last decade. Also, these twoareas are mutually reinforcing, because MCMC methods are oftennecessary for the practical implementation of spatial statisticalinference, while new spatial stochastic models in turn motivate thedevelopment of improved MCMC algorithms.This volume shows how sophisticated spatial statistical andcomputational methods apply to a range of problems of increasingimportance for applications in science and technology. It consists offour chapters: 1. Petros Dellaportas and Gareth O. Roberts give atutorial on MCMC methods, the computational methodology which isessential for virtually all the complex spatial models to beconsidered in subsequent chapters. 2. Peter J. Diggle, Paulo JRibeiro Jr., and Ole F. Christensen introduce the reader to the modelbased approach to geostatistics, i.e. the application of generalstatistical principles to the formulation of explicit stochasticmodels for geostatistical data, and to inference within a declaredclass of models. 3. Merrilee A. Hurn, Oddvar K. Husby, and H vard Ruediscuss various aspects of image analysis, ranging from low to highlevel tasks, and illustrated with different examples of applications.4. Jesper Moller and Rasmus P. Waggepetersen collect recenttheoretical advances in simulation-based inference for spatial pointprocesses, and discuss some examples of applications.The volume introduces topics of current interest in spatial andcomputational statistics, which should be accessible to postgraduatestudents as well as to experienced statistical researchers. It ispartly based on the course material for the 'TMR and MaPhySto SummerSchool on Spatial Statistics and Computational Methods,' held atAalborg University, Denmark, August 19-22, 2001.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 224 pp. Englisch.

Bestandsnummer des Verkäufers 9780387001364

Bibliografische Details

• Titel: Spatial Statistics and Computational Methods
• Verlag: Springer New York, Springer US Mär 2003
• Erscheinungsjahr: 2003
• Sprache: Englisch
• ISBN-10: 0387001360
• ISBN-13: 9780387001364
• Einband: Taschenbuch
• Zustand: Neu

Über diesen Titel

Inhaltsangabe

This volume shows how sophisticated spatial statistical and computational methods apply to a range of problems of increasing importance for applications in science and technology. It introduces topics of current interest in spatial and computational statistics, which should be accessible to postgraduate students as well as to experienced statistical researchers.

Críticas

"This book is a compilation of lecture notes from a number of distinguished professors from the United States, England, France, and Germany. This type of publication in statistics is specifically useful for postgraduate students and scientists."

"Spatial Statistics and Computational Methods successfully presents and updates the recent theoretical advances accompanied by examples and applications in simulation-based inferences. This book will be of practical use for many readers, particularly graduate students." Technometrics, February 2004

"An impressive team of 10 experts wrote this book's four informative chapters on modern computational methods in spatial statistics...Spatial Statistics and Computational Methods...enjoys the clarity of organization and exposition that would make it a suitable main reference for a graduate course in modern methods in spatial statistics." Journal of the American Statistical Association, September 2004

"I found this book to be a valuable contribution...MCMC and spatial statistics have undergone major development over the past ten years. The tutorials covered in this book capture some of these developments and present them in a manner that is accessible to the statistically minded scientific community." Environmetrics Newsletter, 2004

"...Provides the reader with a very good overview of MCMC methodology...it can serve as a reading material for a graduate course that discusses these topics...Well-written chapter[s]." Journal of Statsitical Software, April 2005