The first practical look at spatial statistics for the scientist and engineer. Designed for the scientific and engineering professional eager to exploit its enormous potential, Statistics for Spatial Data is a primer to the theory as well as the nuts–and–bolts of this influential technique. Focusing on the three areas of geostatistical data, lattice data, and point patterns, the book sheds light on the link between data and model, and reveals how spatial statistical models can be used to solve a host of problems in science and engineering. Revised to reflect state–of–the–art developments, this edition also features many detailed examples, numerous illustrations, and over 1,000 references. The first fully comprehensive introduction, Statistics for Spatial Data is an essential guide for professionals in biology, earth science, civil, electrical, and agricultural engineering, geography, epidemiology, and ecology. "This excellent book, which presents the most important branches of modern spatial statistics in an exemplary manner, will become a basic reference book and will popularize many methods which have been used until now only by small circles of specialists." –Mathematical Reviews "The majority of geoscientists should make sure they have access to this volume, while for those who are actively involved in applying statistical methods to data (of all sorts) this book should be in their personal libraries. As a compendium of statistical procedures to use to analyze data, this volume will surely provide a good solid framework for some time to come." –Geophysics
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"This book should be bought. It is a landmark in statistical literature, a comprehensive discourse on a topic previously mostly in the domain of nonstatisticians." (Technometrics, Vol. 36 No. 4, Nov. 1994)
NOEL A.C. CRESSIE is Professor of Statistics at Iowa State University. He has previously served as Lecturer and Senior Lecturer of Mathematics at the Flinders University of South Australia. A fellow of the American Statistical Association and the Institute of Mathematical Statistics, Dr. Cressie is coauthor of Goodness–of–Fit Statistics for Discrete Multivariate Data. He received his PhD in statistics from Princeton University.
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