Identifying Multiple Cluster Structures in a Data Matrix

DOI10.1081/SAC-120023883zbMath1100.62581MaRDI QIDQ4431296

Gabriele Soffritti

Publication date: 19 October 2003

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (4)

An automated robust algorithm for clustering multivariate data ⋮ Modelling the role of variables in model-based cluster analysis ⋮ Finite mixture models for clustering multilevel data with multiple cluster structures ⋮ Model-based methods to identify multiple cluster structures in a data set

Uses Software

• AS 144
• AS 159

Cites Work

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• Algorithm AS 159: An Efficient Method of Generating Random R × C Tables with Given Row and Column Totals
• The dip test of unimodality
• Optimal variable weighting for hierarchical clustering: An alternating least-squares algorithm
• Synthesized clustering: A method for amalgamating alternative clustering bases with differential weighting of variables
• MAPCLUS: A mathematical programming approach to fitting the ADCLUS model
• Partitions of partitions
• Cluster analysis and mathematical programming
• Additive clustering and qualitative factor analysis methods for similarity matrices
• Weighting and selection of variables for cluster analysis
• One-mode classification of a three-way data matrix
• Excess Mass Estimates and Tests for Multimodality
• Algorithm AS 144: Random R × C Tables with Given Row and Column Totals
• Clarification and Appropriate Inferences for Mantel and Valand's Nonparametric Multivariate Analysis Technique
• Permutation methods. A distance function approach

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