References

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

Arnold, S. J. (1979), “A Test for Clusters,” Journal of Marketing Research, 16, 545–551.

Art, D., Gnanadesikan, R., and Kettenring, R. (1982), “Data-Based Metrics for Cluster Analysis,” Utilitas Mathematica, 75–99.

Banfield, J. D. and Raftery, A. (1993), “Model-Based Gaussian and Non-Gaussian Clustering,” Biometrics, 49, 803–821.

Bensmail, H., Celeux, G., Raftery, A. E., and Robert, C. P. (1997), “Inference in Model-Based Cluster Analysis,” Statistics and Computing, 7, 1–10.

Bezdek, J. C. (1981), Pattern Recognition with Fuzzy Objective Function Algorithms, New York: Plenum Press.

Bezdek, J. C. and Pal, S. K. (1992), Fuzzy Models for Pattern Recognition, New York: IEEE Press.

Binder, D. A. (1978), “Bayesian Cluster Analysis,” Biometrika, 65, 31–38.

Binder, D. A. (1981), “Approximations to Bayesian Clustering Rules,” Biometrika, 68, 275–285.

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

Bock, H. H. (1985), “On Some Significance Tests in Cluster Analysis,” Journal of Classification, 2, 77–108.

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), “The Effect of Error on Determining the Number of Clusters,” in Proceedings of the International Workshop on Data Analysis, Decision Support, and Expert Knowledge Representation in Marketing and Related Areas of Research.

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

Duran, B. S. and Odell, P. L. (1974), Cluster Analysis, New York: Springer-Verlag.

Englemann, L. and Hartigan, J. A. (1969), “Percentage Points of a Test for Clusters,” Journal of the American Statistical Association, 64, 1647–1648.

Everitt, B. S. (1979), “Unresolved Problems in Cluster Analysis,” Biometrics, 35, 169–181.

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

Everitt, B. S. (1981), “A Monte Carlo Investigation of the Likelihood Ratio Test for the Number of Components in a Mixture of Normal Distributions,” Multivariate Behavioral Research, 16, 171–80.

Everitt, B. S. and Hand, D. J. (1981), Finite Mixture Distributions, Chapman & Hall.

Gersho, A. and Gray, R. M. (1992), Vector Quantization and Signal Compression, Kluwer Academic Publishers.

Girman, C. J. (1994), Cluster Analysis and Classification Tree Methodology as an Aid to Improve Understanding of Benign Prostatic Hyperplasia, Ph.D. thesis, University of North Carolina, department of Biostatistics.

Good, I. J. (1977), The Botryology of Botryology, in Classification and Clustering, New York: Academic Press.

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. (1978), “Asymptotic Distributions for Clustering Criteria,” Annals of Statistics, 6, 117–131.

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

Hartigan, J. A. (1985a), “Statistical Theory in Clustering,” Journal of Classification, 2, 63–76.

Hartigan, J. A. and Hartigan, P. M. (1985), “The Dip Test of Unimodality,” Annals of Statistics, 13, 70–84.

Hartigan, P. M. (1985b), “Computation of the Dip Statistic to Test for Unimodality,” Applied Statistics, 34, 320–325.

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.

Hubert, L. (1974), “Approximate Evaluation Techniques for the Single-Link and Complete-Link Hierarchical Clustering Procedures,” Journal of the American Statistical Association, 69, 698–704.

Hubert, L. J. and Baker, F. B. (1977), An Empirical Comparison of Baseline Models for Goodness-of-Fit in -Diameter Hierarchical Clustering, in Classification and Clustering, New York: Academic Press.

Kaufman, L. and Rousseeuw, P. J. (1990), Finding Groups in Data, New York: John Wiley & Sons.

Klastorin, T. D. (1983), “Assessing Cluster Analysis Results,” Journal of Marketing Research, 20, 92–98.

Lee, K. L. (1979), “Multivariate Tests for Clusters,” Journal of the American Statistical Association, 74, 708–714.

Ling, R. F. (1973), “A Probability Theory of Cluster Analysis,” Journal of the American Statistical Association, 68, 159–169.

MacQueen, J. B. (1967), “Some Methods for Classification and Analysis of Multivariate Observations,” Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability, 1, 281–297.

Marriott, F. H. C. (1971), “Practical Problems in a Method of Cluster Analysis,” Biometrics, 27, 501–514.

Marriott, F. H. C. (1975), “Separating Mixtures of Normal Distributions,” Biometrics, 31, 767–769.

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

McClain, J. O. and Rao, V. R. (1975), “CLUSTISZ: A Program to Test for the Quality of Clustering of a Set of Objects,” Journal of Marketing Research, 12, 456–460.

McLachlan, G. J. and Basford, K. E. (1988), Mixture Models, New York: Marcel Dekker.

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

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. (1981), “A Review of Monte Carlo Tests of Cluster Analysis,” Multivariate Behavioral Research, 16, 379–407.

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.

Minnotte, M. C. (1992), A Test of Mode Existence with Applications to Multimodality, Ph.D. thesis, Rice University, Department of Statistics, Houston, TX.

Müller, D. W. and Sawitzki, G. (1991), “Excess Mass Estimates and Tests for Multimodality,” Journal of the American Statistical Association, 86, 738–746.

Pollard, D. (1981), “Strong Consistency of k -Means Clustering,” Annals of Statistics, 9, 135–140.

Polonik, W. (1993), Measuring Mass Concentrations and Estimating Density Contour Clusters—An Excess Mass Approach, Technical Report 7, Beitraege zur Statistik, Universitaet Heidelberg.

Sarle, W. S. (1982), “Cluster Analysis by Least Squares,” in Proceedings of the Seventh Annual SAS Users Group International Conference, 651–653, Cary, NC: SAS Institute Inc.

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

Scott, A. J. and Symons, M. J. (1971), “Clustering Methods Based on Likelihood Ratio Criteria,” Biometrics, 27, 387–397.

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

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

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

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

Thode, J., H. C., Mendell, N. R., and Finch, S. J. (1988), “Simulated Percentage Points for the Null Distribution of the Likelihood Ratio Test for a Mixture of Two Normals,” Biometrics, 44, 1195–1201.

Titterington, D. M., Smith, A. F. M., and Makov, U. E. (1985), Statistical Analysis of Finite Mixture Distributions, New York: John Wiley & Sons.

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

Wolfe, J. H. (1970), “Pattern Clustering by Multivariate Mixture Analysis,” Multivariate Behavioral Research, 5, 329–350.

Wolfe, J. H. (1978), “Comparative Cluster Analysis of Patterns of Vocational Interest,” Multivariate Behavioral Research, 13, 33–44.

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.