Hierarchical clustering of variables: a comparison among strategies of analysis

DOI10.1080/03610919908813588zbMath0968.62522OpenAlexW2002475445MaRDI QIDQ4488762

Gabriele Soffritti

Publication date: 9 July 2000

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

Full work available at URL: https://doi.org/10.1080/03610919908813588

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Classification and discrimination; cluster analysis (statistical aspects) (62H30)

Related Items (5)

Clustering of Variables Around Latent Components ⋮ Model-based methods to identify multiple cluster structures in a data set ⋮ Gaussian mixture model with an extended ultrametric covariance structure ⋮ A von Mises-Fisher mixture model for clustering numerical and categorical variables ⋮ Clustering of Variables Based on Watson Distribution on Hypersphere: A Comparison of Algorithms

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• Understanding Canonical Correlation through the General Linear Model and Principal Components
• MEASURING THE RELATIONSHIP BETWEEN TWO SETS OF VARIABLES

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