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RECORD NUMBER: 24 OF 38

OLS Field Name OLS Field Data
Main Title Model-based geostatistics /
Author Diggle, Peter.
Other Authors
Author Title of a Work
Ribeiro, Paulo J.
Publisher Springer,
Year Published 2007
OCLC Number 71284654
ISBN 0387329072; 9780387329079
Subjects Geology--Statistical methods. ; Geology--Mathematical models. ; Geostatistik.--(DE-588)4020279-3 ; Geovetenskap.
Internet Access
Description Access URL
http://www.loc.gov/catdir/enhancements/fy0818/2006927417-d.html
Table of contents http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&doc_number=014996433&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Table of contents http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=014996433&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA
Publisher description http://catdir.loc.gov/catdir/enhancements/fy0818/2006927417-d.html
Inhaltstext http://deposit.ddb.de/cgi-bin/dokserv?id=2803937&prov=M&dok_var=1&dok_ext=htm
Holdings
Library Call Number Additional Info Location Last
Modified
Checkout
Status
EKBM  QE33.2.S82D54 2007 Research Triangle Park Library/RTP, NC 11/23/2009
Collation xiii, 228 pages : illustrations, maps ; 25 cm.
Notes
Includes bibliographical references (pages 218-226) and index.
Contents Notes
Introduction -- An overview of model-based statistics -- Gaussian models for geostatistical data -- Generalized linear models for geostatistical data -- Classical parameter estimation -- Spatial prediction -- Bayesian inference -- Geostatistical design -- A statistical background. This volume is the first book-length treatment of model-based geostatistics. The text is expository, emphasizing statistical methods and applications rather than the underlying mathematical theory. Analyses of datasets from a range of scientific contexts feature prominently, and simulations are used to illustrate theoretical results. Readers can reproduce most of the computational results in the book by using the authors' software package, geoR, whose usage is illustrated in a computation section at the end of each chapter. The book assumes a working knowledge of classical and Bayesian methods of inference, linear models, and generalized linear models.