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Hierarchical Cluster Methods as Maximum Likelihood Estimators

  • Published:1983 Issue: Volume: Page:249-253
  • ISSN:
  • Container-title:Numerical Taxonomy
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Author:

Degens Paul O.

Publisher

Springer Berlin Heidelberg

Reference7 articles.

1. Bock, N.H. 1974. Automatische Klassifikation. Vandenhoek 8 Ruprecht, G?ttingen.

2. Degens, P.O. 1982. Hierarchische Clustermethoden als Maximum Likelihood Schätzer. Arbeitsbericht, Abteilung Statistik, Universität Dortmund.

3. Degens, P.O., and H. Federkiel. 1978. A Monte Carlo study on agglomerative large sample clustering. Compstat 78: 246–252.

4. Physika Verlag Wien. Hartigan, J.A. 1967. Representation of similarity matrices by trees. JASA 62: 1140–1158.

5. Jardine, N., and R. Sibson. 1968. The construction of hierarchic and non-hierarchic classifications. Computer J. 11: 177–184.

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1. On the Optimization Principle in Phylogenetic Analysis and the Minimum-Evolution Criterion;Molecular Biology and Evolution;2000-03-01

2. Data Model and Classification by Trees;Studies in Classification, Data Analysis, and Knowledge Organization;1999

3. Classification and Clustering: Problems for the Future;New Approaches in Classification and Data Analysis;1994

4. A new approach to isotonic agglomerative hierarchical clustering;Journal of Classification;1991-12

5. Interpretation of Hierarchical Clustering;Eurocourses: Chemical and Environmental Science;1991
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