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Geographically Weighted Regression: The Analysis of Spatially Varying Relationships
Geographical Weighted Regression (GWR) is a new local modellingtechnique for analysing spatial analysis. This technique allowslocal as opposed to global models of relationships to be measuredand mapped. This is the first and only book on this technique,offering comprehensive coverage on this new 'hot' topic in spatialanalysis.
* Provides step-by-step examples of how to use the GWR model usingdata sets and examples on issues such as house price determinants,educational attainment levels and school performance statistics
* Contains a broad discussion of and basic concepts on GWR throughto ideas on statistical inference for GWR models
* uniquely features accompanying author-written software thatallows users to undertake sophisticated and complex forms of GWRwithin a user-friendly, Windows-based, front-end (see book fordetails).
* Provides step-by-step examples of how to use the GWR model usingdata sets and examples on issues such as house price determinants,educational attainment levels and school performance statistics
* Contains a broad discussion of and basic concepts on GWR throughto ideas on statistical inference for GWR models
* uniquely features accompanying author-written software thatallows users to undertake sophisticated and complex forms of GWRwithin a user-friendly, Windows-based, front-end (see book fordetails).
288 pages, Hardcover
First published October 11, 2002
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March 25, 2019
A solid reference book that details the relatively new (for its time) spatial statistical approach of geographically weighting attribute values to be regressed. Authors provide enough background to get readers familiar with foundational concepts, then launch into the math behind GWR. The examples provided focus on the UK, utilizing data relating to housing, demographics, and weather – accessible themes that everyone can understand what would be expected at multiple scales.
Where the book suffers is in its lack of bridging the foundation with the equation-heavy math. Numerous times the authors introduce terms included in equations without explaining them. Rather, it feels as though they expected readers to have innate knowledge of some pretty esoteric statistical terminology. Like innumerable math teachers, they speed ahead without ensuring a majority of understanding from the audience. The book also suffers from jamming way too many subtopics into the various chapters. Additionally, the chapter explaining use of the custom software did not age gracefully, and was deprecated fairly rapidly; newest version before discontinued support is several years old, and lacks integration with other, much needed software processing functionality.
Nevertheless, despite its editorial faults, Geographically Weighted Regression: The Analysis of Spatially Varying Relationships by Fotheringham is a useful reference to have for the geospatially driven researcher. As one’s knowledge and experience rises in the field, more and more of this book opens up its secrets. I can imagine it certainly entices quantitative geographers to delve deeply into GWR, regardless of applicability to current research.
Where the book suffers is in its lack of bridging the foundation with the equation-heavy math. Numerous times the authors introduce terms included in equations without explaining them. Rather, it feels as though they expected readers to have innate knowledge of some pretty esoteric statistical terminology. Like innumerable math teachers, they speed ahead without ensuring a majority of understanding from the audience. The book also suffers from jamming way too many subtopics into the various chapters. Additionally, the chapter explaining use of the custom software did not age gracefully, and was deprecated fairly rapidly; newest version before discontinued support is several years old, and lacks integration with other, much needed software processing functionality.
Nevertheless, despite its editorial faults, Geographically Weighted Regression: The Analysis of Spatially Varying Relationships by Fotheringham is a useful reference to have for the geospatially driven researcher. As one’s knowledge and experience rises in the field, more and more of this book opens up its secrets. I can imagine it certainly entices quantitative geographers to delve deeply into GWR, regardless of applicability to current research.
Displaying 1 of 1 review