A Casebook for Spatial Statistical Data Analysis: A Compilation of Analyses of Different Thematic…

Hardcover | October 15, 1999

byDaniel A. Griffith, Larry J. Layne

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This volume compiles geostatistical and spatial autoregressive data analyses involving georeferenced socioeconomic, natural resources, agricultural, pollution, and epidemiological variables. Benchmark analyses are followed by analyses of readily available data sets, emphasizing parallelsbetween geostatistical and spatial autoregressive findings. Both SAS and SPSS code are presented for implementation purposes. This informative casebook will serve geographers, regional scientists, applied spatial statisticians, and spatial scientists from across disciplines.

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This volume compiles geostatistical and spatial autoregressive data analyses involving georeferenced socioeconomic, natural resources, agricultural, pollution, and epidemiological variables. Benchmark analyses are followed by analyses of readily available data sets, emphasizing parallelsbetween geostatistical and spatial autoregressive...

Daniel A. Griffith is at Syracuse University.

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Format:HardcoverPublished:October 15, 1999Publisher:Oxford University PressLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:0195109589

ISBN - 13:9780195109580

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Table of Contents

IntroductionList of AbbreviationsPart I: Theoretical Background1. Introduction2. Important Modeling Assumptions3. Popular Spatial Autoregressive and Geostatistical ModelsPart II: Georeferenced Data Set Case Studies4. Analysis of Georeferenced Socioeconomic Attribute Variables5. Analysis of Georeferenced Natural Resources Attribute Variables6. Analysis of Georeferenced Agricultural Yield Variables7. Analysis of Georeferenced Pollution Variables8. Analysis of Georeferenced Epidemiological VariablesPart III: Visualizing What is Not Observed9. Exploding Georeferenced Data When Maps Have Holes or Gaps: Estimating Missing Data Values and Kriging10. Concluding CommentsEpilogueBibliographyIndex