Computer Programs
Brusco, M., & Steinley, D. (submitted). Neighborhood search heuristics for selecting hierarchically well-formulated subsets in polynomial regression.
Koehn, H.-F., Steinley, D., & Brusco, M. (submitted). The p-median model as a tool for clustering psychological data. -The file below contains some software programs and a user’s manual for p-median clustering.
Brusco, M., Steinley, D., & Cradit, J. D. (in press). An exact algorithm for hierarchically well-formulated subsets in second-order polynomial regression. To appear in Technometrics.
Brusco, M., & Koehn, H.-F. (submitted). Clustering qualitative data based on binary equivalence relations: Neighborhood search heuristics for the clique partitioning problem. To appear in Psychometrika.
Brusco, M., & Koehn, H.-F. (2008). Comment on ‘Clustering by Passing Messages Between Data Points’. Science, 319 (February 8), p. 726.
Overview of methods and summary of comparison
Vertex substitution heuristic (a Matlab m-file)
VSH version that ignores preference vector (a Matlab m-file)
Hartigans birth and death rates data
European cities (202) data from Grotschel and Holland
European cities (431) data from Grotschel and Holland
European cities (666) data from Grotschel and Holland
Reinelts circuit board holes data
Brusco, M., & Stahl, S. (2005). Branch-and-Bound Applications in Combinatorial Data Analysis.
Minimum diameter partitioning (Chapter 3)
Minimum within-cluster sums of dissimilarities partitioning (Chapter 4)
Minimum within-cluster sums of squares partitioning (Chapter 5)
Bicriterion within-cluster sums of squares (Chapter 6)
Maximizing the dominance index (Chapter 8)
Maximizing gradient indices (Chapter 9)
Unidimensional Scaling (Chapter 10)
Brusco, M., & Cradit, J. D. (2005). Bicriterion methods for partitioning dissimilarity matrices. British Journal of Mathematical and Statistical Psychology, 58, 319-332.