Clustering in Time and Space

  • Phillip Good
Part of the Springer Series in Statistics book series (SSS)

Abstract

In this chapter, you learn how to detect clustering in time and space and to validate clustering models. We use the generalized quadratic form in its several guises including Mantel’s U and Mielke’s multi-response permutation procedure to work through a series of applications in atmospheric science, epidemiology, ecology, and archeology.

Keywords

Archaeological Artifact Permutation Distribution Interpoint Distance Sample Correlation Matrix Symmetric Volume 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Science+Business Media New York 1994

Authors and Affiliations

  • Phillip Good
    • 1
  1. 1.Huntington BeachUSA

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