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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 multiresponse permutation procedure to work through a series of applications in atmospheric science, epidemiology, ecology, and archeology.

Keywords

Permutation Distribution Interpoint Distance Sample Correlation Matrix Random Rearrangement Straight Line Rela 
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 2000

Authors and Affiliations

  • Phillip Good
    • 1
  1. 1.Huntington BeachUSA

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