Drawing on applied statistics, mathematical statistics, linear model theory, regression, time series and stochastic processes, the authors, practicing statisticians, examine theories and methods for spatial data analysis. They start by describing theories on random fields, and go on to mapped point patterns, semivariogram and covariance function analysis and estimation, spatial prediction and Kriging, spatial regression models, simulation of random fields, non-stationary covariance, and spatio-temporal processes. They include exercises for each chapter and references. Annotation ©2004 Book News, Inc., Portland, OR (booknews.com)