Advanced Spatial Statistics

Special Topics in the Exploration of Quantitative Spatial Data Series

  • Daniel A. Griffith

Part of the Advanced Studies in Theoretical and Applied Econometrics book series (ASTA, volume 12)

Table of contents

  1. Front Matter
    Pages I-XIV
  2. Daniel A. Griffith
    Pages 24-40
  3. Daniel A. Griffith
    Pages 82-107
  4. Daniel A. Griffith
    Pages 108-126
  5. Daniel A. Griffith
    Pages 200-224
  6. Daniel A. Griffith
    Pages 225-260
  7. Daniel A. Griffith
    Pages 261-269
  8. Back Matter
    Pages 271-274

About this book


In recent years there has been a growing interest in and concern for the development of a sound spatial statistical body of theory. This work has been undertaken by geographers, statisticians, regional scientists, econometricians, and others (e. g. , sociologists). It has led to the publication of a number of books, including Cliff and Ord's Spatial Processes (1981), Bartlett's The Statistical Analysis of Spatial Pattern (1975), Ripley's Spatial Statistics (1981), Paelinck and Klaassen's Spatial Economet~ics (1979), Ahuja and Schachter's Pattern Models (1983), and Upton and Fingleton's Spatial Data Analysis by Example (1985). The first of these books presents a useful introduction to the topic of spatial autocorrelation, focusing on autocorrelation indices and their sampling distributions. The second of these books is quite brief, but nevertheless furnishes an eloquent introduction to the rela­ tionship between spatial autoregressive and two-dimensional spectral models. Ripley's book virtually ignores autoregressive and trend surface modelling, and focuses almost solely on point pattern analysis. Paelinck and Klaassen's book closely follows an econometric textbook format, and as a result overlooks much of the important material necessary for successful spatial data analy­ sis. It almost exclusively addresses distance and gravity models, with some treatment of autoregressive modelling. Pattern Models supplements Cliff and Ord's book, which in combination provide a good introduction to spatial data analysis. Its basic limitation is a preoccupation with the geometry of planar patterns, and hence is very narrow in scope.


Simulation Statistical Models calculus efficiency statistics

Authors and affiliations

  • Daniel A. Griffith
    • 1
  1. 1.University of New YorkBuffaloUSA

Bibliographic information

  • DOI
  • Copyright Information Springer Science+Business Media B.V. 1988
  • Publisher Name Springer, Dordrecht
  • eBook Packages Springer Book Archive
  • Print ISBN 978-94-010-7739-2
  • Online ISBN 978-94-009-2758-2
  • Series Print ISSN 1570-5811
  • Buy this book on publisher's site