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Inference Procedures for the Evaluation and Comparison of Proximity Matrices

  • Chapter
Numerical Taxonomy

Part of the book series: NATO ASI Series ((ASIG,volume 1))

Abstract

As the title suggests, this paper is concerned with proximity matrices, or more explicitly, with any matrix that contains numerical values indexing the relationship between objects from some given set. Since the methods of evaluation to be discussed have a number of uses, our review could be appropriately placed under a particular subtopic such as hierarchical clustering, or within a more inclusive framework such as classification analysis. Alternatively, the discussion has major implications for studying geographical variation, and thus, it could be presented in this context as well. Instead of delineating any one class of special cases at the expense of others, the analysis strategies will be phrased for arbitrary proximity matrices, whatever their source. Specific interpretations will be mentioned throughout to help clarify the variety of possible applications.

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Author information

Authors and Affiliations

  1. Graduate School of Education, University of California, Santa Barbara, Santa Barbara, California, 93106, USA

    Lawrence J. Hubert

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  1. Lawrence J. Hubert
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Editor information

Editors and Affiliations

  1. Department of Genetics, University of Washington, 98195, Seattle, Washington, USA

    Joseph Felsenstein

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© 1983 Springer-Verlag Berlin Heidelberg

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Hubert, L.J. (1983). Inference Procedures for the Evaluation and Comparison of Proximity Matrices. In: Felsenstein, J. (eds) Numerical Taxonomy. NATO ASI Series, vol 1. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-69024-2_27

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  • DOI: https://doi.org/10.1007/978-3-642-69024-2_27

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-69026-6

  • Online ISBN: 978-3-642-69024-2

  • eBook Packages: Springer Book Archive

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