Hierarchical Modeling and Analysis for Spatial Data

Sudipto Banerjee, Bradley P. Carlin, Alan E. Gelfand

Chapman and Hall/CRC
Published September 12, 2014
Reference - 584 Pages - 177 Color Illustrations
ISBN 9781439819173 - CAT# K11011
Series: Chapman & Hall/CRC Monographs on Statistics & Applied Probability

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  • Presents a fully model-based approach to all areas of spatial statistics, including point level, areal, and point pattern data
  • Incorporates four new chapters, along with a host of updates and additions
  • Offers a practical introduction to point-referenced modeling as well as some theory for those who would like more insight into the issues that arise in the geostatistical setting
  • Uses up-to-date WinBUGS programs and R packages for exploratory data analysis and hierarchical modeling
  • Indicates advanced/theoretical material that may be skipped by readers wanting to focus on more practical aspects
  • Provides datasets and code on a supplementary website


Keep Up to Date with the Evolving Landscape of Space and Space-Time Data Analysis and Modeling

Since the publication of the first edition, the statistical landscape has substantially changed for analyzing space and space-time data. More than twice the size of its predecessor, Hierarchical Modeling and Analysis for Spatial Data, Second Edition reflects the major growth in spatial statistics as both a research area and an area of application.

New to the Second Edition

  • New chapter on spatial point patterns developed primarily from a modeling perspective
  • New chapter on big data that shows how the predictive process handles reasonably large datasets
  • New chapter on spatial and spatiotemporal gradient modeling that incorporates recent developments in spatial boundary analysis and wombling
  • New chapter on the theoretical aspects of geostatistical (point-referenced) modeling
  • Greatly expanded chapters on methods for multivariate and spatiotemporal modeling
  • New special topics sections on data fusion/assimilation and spatial analysis for data on extremes
  • Double the number of exercises
  • Many more color figures integrated throughout the text
  • Updated computational aspects, including the latest version of WinBUGS, the new flexible spBayes software, and assorted R packages

The Only Comprehensive Treatment of the Theory, Methods, and Software

This second edition continues to provide a complete treatment of the theory, methods, and application of hierarchical modeling for spatial and spatiotemporal data. It tackles current challenges in handling this type of data, with increased emphasis on observational data, big data, and the upsurge of associated software tools. The authors also explore important application domains, including environmental science, forestry, public health, and real estate.


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