Advertisement

A Regression Analytic Modification of Ward’s Method: A Contribution to the Relation between Cluster Analysis and Factor Analysis

  • S. Krolak-Schwerdt
  • P. Orlik
  • A. Kohler
Part of the Studies in Classification, Data Analysis, and Knowledge Organization book series (STUDIES CLASS)

Abstract

A regression analytic modification of the minimum variance method (Ward’s method) is outlined. In the proposed method the within-cluster sums of squares are partitioned into the proportion accounted for by the cluster centers and the residual variation. The procedure consists of fusing the two clusters that minimize the residual variation not predicted by the centers. The method allows for a combination of clustering and factor analysis in order to determine the kind of properties that govern the relationships between the clusters.

Keywords

Residual Variation Dimensional Representation Multivariate Observation Minimum Prediction Error Minimum Variance Method 
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.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Bibliography

  1. Eckes, T., Rossbach, H. (1980): Clusteranalysen. Kohlhammer, Stuttgart, pp. 74–76.zbMATHGoogle Scholar
  2. Everitt, B.S. (1979): Unresolved Problems in Cluster Analysis. Biometrics, 35, pp. 169–181.zbMATHGoogle Scholar
  3. Fillenbaum, S., Rapoport, A. (1971): Structures in the Subjective Lexicon. Academic Press, New York, pp. 140–150.Google Scholar
  4. Harman, H.H. (1965): Modern factor analysis. The University of Chicago Press, Chicago, pp. 192–230.Google Scholar
  5. Hays, W.L. (1973): Statistics for the social sciences. Holt, Binehart & Winston, New York, pp. 616–716.Google Scholar
  6. Horst, P. (1965): Factor analysis of data matrices. Holt, Rinehart & Winston, New York, pp. 114–155.zbMATHGoogle Scholar
  7. Jain, A.K., Dubes, R.C. (1988): Algorithms for Clustering Data. Prentice Hall, Englewood Cliffs, N.J., pp. 7–54.Google Scholar
  8. Revenstorf, D. (1980): Faktorenanalyse. Kohlhammer, Stuttgart, pp. 128–140.zbMATHGoogle Scholar
  9. Seber, G.A.F. (1984): Multivariate observations. Wiley, New York, pp. 347–394.zbMATHGoogle Scholar
  10. Stange, K. (1971): Angewandte Statistik. Mehrdimensionale Probleme. Springer, Heidelberg, pp. 121–178.Google Scholar
  11. Wishart, D. (1969): An algorithm for hierarchical classifications. Biometrics, 28, pp. 165–170.Google Scholar

Copyright information

© Springer-Verlag Berlin · Heidelberg 1991

Authors and Affiliations

  • S. Krolak-Schwerdt
    • 1
  • P. Orlik
    • 1
  • A. Kohler
    • 1
  1. 1.Psychologisches InstitutUniversität des SaarlandesSaarbrückenGermany

Personalised recommendations