Hierarchical Modeling and Analysis for Spatial Data (Monographs on Statistics and Applied Probability) | 
 enlarge | Authors: Sudipto Banerjee, Bradley. P. Carlin, Alan E. Gelfand
Publisher: Chapman & Hall/CRC
Category: Book
List Price: $88.95
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Rating:  1 reviews
Sales Rank: 412134
Media: Hardcover
Edition: 1
Pages: 472
Number Of Items: 1
Shipping Weight (lbs): 1.7
Dimensions (in): 9.1 x 5.9 x 1.2
ISBN: 158488410X
Dewey Decimal Number: 519.5
EAN: 9781584884101
Publication Date: December 17, 2003
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Product Description
Among the many uses of hierarchical modeling, their application to the statistical analysis of spatial and spatio-temporal data from areas such as epidemiology And environmental science has proven particularly fruitful. Yet to date, the few books that address the subject have been either too narrowly focused on specific aspects of spatial analysis, or written at a level often inaccessible to those lacking a strong background in mathematical statistics.Hierarchical Modeling and Analysis for Spatial Data is the first accessible, self-contained treatment of hierarchical methods, modeling, and data analysis for spatial and spatio-temporal data. Starting with overviews of the types of spatial data, the data analysis tools appropriate for each, and a brief review of the Bayesian approach to statistics, the authors discuss hierarchical modeling for univariate spatial response data, including Bayesian kriging and lattice (areal data) modeling. They then consider the problem of spatially misaligned data, methods for handling multivariate spatial responses, spatio-temporal models, and spatial survival models. The final chapter explores a variety of special topics, including spatially varying coefficient models.This book provides clear explanations, plentiful illustrations --some in full color--a variety of homework problems, and tutorials and worked examples using some of the field's most popular software packages.. Written by a team of leaders in the field, it will undoubtedly remain the primary textbook and reference on the subject for years to come.
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| Customer Reviews:
A key text on Bayesian spatial statistics November 13, 2005
A. Finley (Twin Cities, MN USA)
12 out of 12 found this review helpful
I've bought several spatial statistics books over the years and found they generally fall into one of two categories; oversimplified or cover-to-cover matrix notation, neither of which is very useful for my research. However, this book is "just right," bridging these two extremes. It briefly covers the basics of both point and areal analysis, then gives the reader the tools for more advanced (i.e., realistic) analysis. They devote a chapter to Bayesian basics, which is needed for the last 4 or 5 chapters. The last few chapters weave together a detailed discussion on a variety of hierarchical models and current published results. Most importantly this book offers quite a bit of the necessary R and Winbugs code. Although many of their examples are from the public health world, the techniques and code are easily adapted to natural resource data - my personal focus.
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