Between-group analysis with heterogeneous covariance matrices: The common principal component model

DOI10.1007/BF01889705zbMath0714.62051MaRDI QIDQ751123

Wojtek Janusz Krzanowski

Publication date: 1990

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

zbMATH Keywords

eigenvaluescanonical variate analysiseigenvectorscommon principal component modelbetween- group analysisMatusita distancemetric scaling

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25)

Related Items (5)

Ordination in the presence of group structure, for general multivariate data ⋮ Recipes for sparse LDA of horizontal data ⋮ On estimating the dimensionality in discriminant analysis ⋮ Estimating common principal components in high dimensions ⋮ Some Observations on the Correlation Determinant

Uses Software

• AS 211

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Decision rule, based on the distance, for the classification problem
• Diversity and dissimilarity coefficients: A unified approach
• Quadratic discrimination: Some results on optimal low-dimensional representation
• The Mahalanobis distance and elliptic distributions
• The comparison of sample covariance matrices using likelihood ratio tests
• Classification into two Multivariate Normal Distributions with Different Covariance Matrices
• Some distance properties of latent root and vector methods used in multivariate analysis
• On the Assumptions Used to Prove Asymptotic Normality of Maximum Likelihood Estimates
• On Information and Sufficiency

This page was built for publication: Between-group analysis with heterogeneous covariance matrices: The common principal component model