“This is an important book bringing together a family of related statistical measures and explaining them in a coherent way. Written by leading researchers in the field, it uses a consistent spatial example and applies and explains various measures within a unifying frame to aid in understanding by readers. As real-time spatial data becomes increasingly prevalent, the need for analysts to accurately and meaningfully interpret this data is rapidly growing."
“The field of spatial regression has grown rapidly over the last decade. This book goes a long way toward filling a gap by providing students and practitioners with a useful text that is written at a level that should make it broadly accessible.”
“This is an exceptionally well-written text on spatial data analysis tailored for social science research. It deals with spatial thinking and regression analysis with remarkable depth and expertise in a comprehensive and easy-to-follow manner. It is a primer that should be on every social scientist's shelf.”
“This introductory book offers a full overview of the different ways in which a standard linear regression model can be extended to contain spatial effects.”
“Spatial data science is an evolving field. This is a valuable book that introduces to students, researchers, and faculty the foundation of spatial statistics and offers tremendous insights on how to statistically analyze geo-spatial data. Anyone working geo-data must read this book if they want accurate and unbiased research findings.”
the book’s main strength is its efficiency, organization, and methodical approach to explaining many concepts in spatial regression. It does not necessarily progress in concept difficulty nor in concept importance, but mixes both to form a coherent volume that is a strong reference for both looking up terms as a “refresher” and as a guide to diversifying one’s own spatial regression techniques for a comparative analysis
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