Publisher: Chapman & Hall/CRC Statistical Methods for Spatial Data Analysis is a comprehensive treatment of statistical theory and methods for spatial data analysis, employing a model-based and frequentist approach that emphasizes the spatial domain. The volume delivers an up-to-date treatment of semivariogram estimation and modeling and spatial analysis in the spectral domain, as well as a thorough analysis of spatial regression, covering linear models with uncorrelated errors, linear models with spatially-correlated errors and generalized linear mixed models for spatial data and succinctly discussing Bayesian hierarchical models. It concludes with a review of simulation, non-stationary covariance and spatio-temporal processes. Review: but accessible if you have the appropriate background. A great treatment of the underlying theory, without too much obfuscation. The authors include many interesting examples and make available SAS code on their website. |