Graph-theoretic representations for proximity matrices through strongly-anti-Robinson or circular strongly-anti-Robinson matrices

DOI10.1007/BF02294859zbMath1291.62215MaRDI QIDQ2248666

Phipps Arabie, Lawrence J. Hubert, Jacqueline J. Meulman

Publication date: 27 June 2014

Published in: Psychometrika (Search for Journal in Brave)

zbMATH Keywords

graphical representationcircular strongly-anti-Robinsonleast-squares matrix approximationstrongly-anti-Robinson

Mathematics Subject Classification ID

Applications of statistics to psychology (62P15)

Related Items

Structural classification analysis of three-way dissimilarity data ⋮ A Simple and Optimal Algorithm for Strict Circular Seriation ⋮ The seriation problem in the presence of a double Fiedler value ⋮ Modules in Robinson Spaces ⋮ On Robinsonian dissimilarities, the consecutive ones property and latent variable models ⋮ Representation of individual differences in rectangular proximity data through anti-Q matrix decomposition ⋮ A branch-and-bound algorithm for fitting anti-Robinson structures to symmetric dissimilarity matrices ⋮ Heuristic implementation of dynamic programming for matrix permutation problems in combinatorial data analysis ⋮ Combinatorial optimisation and hierarchical classifications ⋮ Optimal least-squares unidimensional scaling: improved branch-and-bound procedures and comparison to dynamic programming ⋮ An Optimal Algorithm for Strict Circular Seriation

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• A sequential fitting procedure for linear data analysis models
• Spatial, non-spatial and hybrid models for scaling
• Mathematical classification and clustering
• An Algorithm for Restricted Least Squares Regression
• Linear and circular unidimensional scaling for symmetric proximity matrices
• Iterative projection strategies for the least‐squares fitting of tree structures to proximity data
• The analysis of proximity matrices through sums of matrices having (anti‐)Robinson forms