Analysis and Modelling of Spatial Environmental Data

The subject of environmental statistics is so broad that it would be virtually impossible to go into sufficient detail in a book of reasonable length. That being said, the book still has some critical omissions. For example, there is no discussion on censored observations. This is a critical concern in many environmental data analysis and modeling problems. Furthermore, there is too little discussion on generalized linear models and no discussion on generalized linear mixed models, in many respects the state-of-the-art approach to real-world response modeling. In addition, there is no serious discussion of Bayesian methods and hierarchical models. Such methods and approaches have revolutionized the study of spatial and spatiotemporal processes, and can be found throughout the environmental science literature over the last 10 years or so. On a related note, there is little mention of environmental issues concerned with human health. Such epidemiologic methodology has progressed dramatically over the past few years and is a major driving force in modern environmental statistics. In general, the author has done a nice job on an ambitious project. This book would be a useful first exposure to traditional environmental statistics for a reader with a reasonably strong background in mathematical statistics.