Hierarchical disjoint principal component analysis

DOI10.1007/s10182-022-00458-4MaRDI QIDQ6065676

Carlo Cavicchia, Giorgia Zaccaria, Maurizio Vichi

Publication date: 15 November 2023

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://pure.eur.nl/en/publications/87fba922-433e-4325-81f8-f0196b834444

zbMATH Keywords

dimension reductionhierarchical modelsreflective modelsparsimonious treesformative models

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• PLS path modeling
• The development of hierarchical factor solutions
• Hierarchical factor solutions without rotation
• Clustering and disjoint principal component analysis
• NP-hard problems in hierarchical-tree clustering
• Sparsest factor analysis for clustering variables: a matrix decomposition approach
• Principal component analysis.
• Coefficient alpha and the internal structure of tests
• The ultrametric correlation matrix for modelling hierarchical latent concepts
• On the relationship between the higher-order factor model and the hierarchical factor model
• Disjoint factor analysis with cross-loadings
• Estimation of a Model with Multiple Indicators and Multiple Causes of a Single Latent Variable
• Clustering of Variables Around Latent Components
• Simple Principal Components
• Advanced Time Series Data Analysis
• Tests for High-Dimensional Covariance Matrices
• Dimensions of Well-Being and Their Statistical Measurements
• A general method for analysis of covariance structures
• A Direct Formulation for Sparse PCA Using Semidefinite Programming

This page was built for publication: Hierarchical disjoint principal component analysis