Anderberg, M. R. (1973), Cluster Analysis for Applications, New York: Academic Press.

Batagelj, V. (1981), “Note on Ultrametric Hierarchical Clustering Algorithms,” Psychometrika, 46, 351–352.

Blackith, R. E. and Reyment, R. A. (1971), Multivariate Morphometrics, London: Academic Press.

Blashfield, R. K. and Aldenderfer, M. S. (1978), “The Literature on Cluster Analysis,” Multivariate Behavioral Research, 13, 271–295.

Calinski, T. and Harabasz, J. (1974), “A Dendrite Method for Cluster Analysis,” Communications in Statistics, 3, 1–27.

Cooper, M. C. and Milligan, G. W. (1988), Data, Expert Knowledge, and Decisions, chapter The Effect of Error on Determining the Number of Clusters, 319–328, London: Springer-Verlag.

Duda, R. O. and Hart, P. E. (1973), Pattern Classification and Scene Analysis, New York: John Wiley & Sons.

Everitt, B. S. (1980), Cluster Analysis, Second Edition, London: Heineman Educational Books.

Fisher, L. and Van Ness, J. W. (1971), “Admissible Clustering Procedures,” Biometrika, 58, 91–104.

Fisher, R. A. (1936), “The Use of Multiple Measurements in Taxonomic Problems,” Annals of Eugenics, 7, 179–188.

Florek, K., Lukaszewicz, J., Perkal, J., and Zubrzycki, S. (1951a), “Sur la Liaison et la Division des Points d’un Ensemble Fini,” Colloquium Mathematicae, 2, 282–285.

Florek, K., Lukaszewicz, J., Perkal, J., and Zubrzycki, S. (1951b), “Taksonomia Wroclawska,” Przeglad Antropol., 17, 193–211.

Gower, J. C. (1967), “A Comparison of Some Methods of Cluster Analysis,” Biometrics, 23, 623–637.

Hamer, R. M. and Cunningham, J. W. (1981), “Cluster Analyzing Profile Data with Interrater Differences: A Comparison of Profile Association Measures,” Applied Psychological Measurement, 5, 63–72.

Hartigan, J. A. (1975), Clustering Algorithms, New York: John Wiley & Sons.

Hartigan, J. A. (1977), “Distribution Problems in Clustering,” in J. V. Ryzin, ed., Classification and Clustering, New York: Academic Press.

Hartigan, J. A. (1981), “Consistency of Single Linkage for High-Density Clusters,” Journal of the American Statistical Association, 76, 388–394.

Hawkins, D. M., Muller, M. W., and ten Krooden, J. A. (1982), “Cluster Analysis,” in D. M. Hawkins, ed., Topics in Applied Multivariate Analysis, Cambridge: Cambridge University Press.

Jardine, N. and Sibson, R. (1971), Mathematical Taxonomy, New York: John Wiley & Sons.

Johnson, S. C. (1967), “Hierarchical Clustering Schemes,” Psychometrika, 32, 241–254.

Lance, G. N. and Williams, W. T. (1967), “A General Theory of Classificatory Sorting Strategies. I. Hierarchical Systems,” Computer Journal, 9, 373–380.

Massart, D. L. and Kaufman, L. (1983), The Interpretation of Analytical Chemical Data by the Use of Cluster Analysis, New York: John Wiley & Sons.

McQuitty, L. L. (1957), “Elementary Linkage Analysis for Isolating Orthogonal and Oblique Types and Typal Relevancies,” Educational and Psychological Measurement, 17, 207–229.

McQuitty, L. L. (1966), “Similarity Analysis by Reciprocal Pairs for Discrete and Continuous Data,” Educational and Psychological Measurement, 26, 825–831.

Mezzich, J. and Solomon, H. (1980), Taxonomy and Behavioral Science, New York: Academic Press.

Milligan, G. W. (1979), “Ultrametric Hierarchical Clustering Algorithms,” Psychometrika, 44, 343–346.

Milligan, G. W. (1980), “An Examination of the Effect of Six Types of Error Perturbation on Fifteen Clustering Algorithms,” Psychometrika, 45, 325–342.

Milligan, G. W. (1987), A Study of the Beta-Flexible Clustering Method, Technical Report 87-61, Ohio State University, Columbus, college of Administrative Science Working Paper Series.

Milligan, G. W. and Cooper, M. C. (1985), “An Examination of Procedures for Determining the Number of Clusters in a Data Set,” Psychometrika, 50, 159–179.

Milligan, G. W. and Cooper, M. C. (1987), A Study of Variable Standardization, Technical Report 87-63, Ohio State University, Columbus, college of Administrative Science Working Paper Series.

Rouncefield, M. (1995), “The Statistics of Poverty and Inequality,” Journal of Statistics Education Data Archive, last accessed May 22, 2009.

Sarle, W. S. (1983), Cubic Clustering Criterion, SAS Technical Report A-108, Cary, NC: SAS Institute Inc.

Silverman, B. W. (1986), Density Estimation for Statistics and Data Analysis, New York: Chapman & Hall.

Sneath, P. H. A. (1957), “The Application of Computers to Taxonomy,” Journal of General Microbiology, 17, 201–226.

Sneath, P. H. A. and Sokal, R. R. (1973), Numerical Taxonomy, San Francisco: Freeman.

Sokal, R. R. and Michener, C. D. (1958), “A Statistical Method for Evaluating Systematic Relationships,” University of Kansas Science Bulletin, 38, 1409–1438.

Sorensen, T. (1948), “A Method of Establishing Groups of Equal Amplitude in Plant Sociology Based on Similarity of Species Content and Its Application to Analyses of the Vegetation on Danish Commons,” Biologiske Skrifter, 5, 1–34.

Spath, H. (1980), Cluster Analysis Algorithms, Chichester, England: Ellis Horwood.

Symons, M. J. (1981), “Clustering Criteria and Multivariate Normal Mixtures,” Biometrics, 37, 35–43.

Ward, J. H. (1963), “Hierarchical Grouping to Optimize an Objective Function,” Journal of the American Statistical Association, 58, 236–244.

Wishart, D. (1969), “Mode Analysis: A Generalisation of Nearest Neighbour Which Reduces Chaining Effects,” in A. J. Cole, ed., Numerical Taxonomy, London: Academic Press.

Wong, M. A. (1982), “A Hybrid Clustering Method for Identifying High-Density Clusters,” Journal of the American Statistical Association, 77, 841–847.

Wong, M. A. and Lane, T. (1983), “A th Nearest Neighbor Clustering Procedure,” Journal of the Royal Statistical Society.

Wong, M. A. and Schaack, C. (1982), “Using the th Nearest Neighbor Clustering Procedure to Determine the Number of Subpopulations,” American Statistical Association 1982 Proceedings of the Statistical Computing Section, 40–48.