Treatments of non-metric variables in partial least squares and principal component analysis

DOI10.1080/02664763.2017.1346065OpenAlexW290191658MaRDI QIDQ5035745

Tatyana Krivobokova, Jisu Yoon

Publication date: 22 February 2022

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

Full work available at URL: http://hdl.handle.net/10419/109027

zbMATH Keywords

partial least squaresprincipal component analysiscomposite indexwealthnon-metric variables

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

Uses Software

• SPSS

Cites Work

• Unnamed Item
• Unnamed Item
• An analysis and synthesis of multiple correspondence analysis, optimal scaling, dual scaling, homogeneity analysis and other methods for quantifying categorical multivariate data
• Non-metric partial least squares
• Uncertainty and Sensitivity Analysis Techniques as Tools for the Quality Assessment of Composite Indicators
• Correspondence Analysis in Practice
• Comparison of prediction methods for multicollinear data

This page was built for publication: Treatments of non-metric variables in partial least squares and principal component analysis