Non-uniqueness and Inversions in Cluster Analysis

DOI10.2307/2986199zbMath0821.62036OpenAlexW1582326668MaRDI QIDQ4842320

Andrew P. G. Ray, Byron J. T. Morgan

Publication date: 3 October 1995

Published in: Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/2986199

zbMATH Keywords

S-PLUScluster analysisUPGMAreversalscentroid methodWard's methodinversionsnonuniquenessSASBMDPSPSSdendrogramspruned treeshierarchical methodsanorexia nervosacomplete link analysisgroup average analysismedian methodNTSYS-pcphenogramssingle-link analysisSTATGRAPHICSUPGMCweighted average analysisWPGMAWPGMC

Mathematics Subject Classification ID

Software, source code, etc. for problems pertaining to statistics (62-04) Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics (62P99)

Related Items (9)

Clustering analysis of gene expression data based on semi-supervised visual clustering algorithm ⋮ Modular decomposition of metabolic systems via null-space analysis ⋮ Rival penalized competitive learning (RPCL): A topology-determining algorithm for analyzing gene expression data. ⋮ Versatile linkage: a family of space-conserving strategies for agglomerative hierarchical clustering ⋮ Mixtures of (constrained) ultrametric trees ⋮ A permutation test for determining significance of clusters with applications to spatial and gene expression data ⋮ Solving non-uniqueness in agglomerative hierarchical clustering using multidendrograms ⋮ Hierarchical time series clustering on tail dependence with linkage based on a multivariate copula approach ⋮ Microarray Data Analysis Using Fuzzy Clustering Algorithms

Uses Software

• STATGRAPHICS
• SPSS
• SAS
• BMDP

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