A latent class procedure for the structural analysis of two-way compositional data

DOI10.1007/BF02626090zbMath0800.62332MaRDI QIDQ1314823

Venkatram Ramaswamy, Peter J. Lenk, Wayne S. Desarbo

Publication date: 1 March 1994

Published in: Journal of Classification (Search for Journal in Brave)

Mathematics Subject Classification ID

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

Related Items (2)

Regression analysis of variates observed on (0, 1): percentages, proportions and fractions ⋮ Dealing with distances and transformations for fuzzy \(c\)-means clustering of compositional data

Cites Work

• A maximum likelihood method for fitting the wandering vector model
• Multi-sample cluster analysis using Akaike's information criterion
• Multiclus: a new method for simultaneously performing multidimensional scaling and cluster analysis
• The wandering ideal point model: A probabilistic multidimensional unfolding model for paired comparisons data
• Model selection and Akaike's information criterion (AIC): The general theory and its analytical extensions
• A new characterization of the Dirichlet distribution through neutrality
• Hierarchical clustering schemes
• A latent class probit model for analyzing pick any/N data
• Exploratory latent structure analysis using both identifiable and unidentifiable models
• Maximum likelihood estimation of dirichlet distributions
• A new look at the statistical model identification
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