A class of new partial least square algorithms for first and higher order models

DOI10.1080/03610918.2020.1741622OpenAlexW3013059659MaRDI QIDQ5867469

Hao Cheng

Publication date: 14 September 2022

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

Full work available at URL: https://doi.org/10.1080/03610918.2020.1741622

zbMATH Keywords

quantile regressionlatent variable modelpartial least square

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (1)

Quantile varying-coefficient structural equation model

Uses Software

• SmartPLS

Cites Work

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• PLS path modeling
• Quantile composite-based path modeling
• The development of hierarchical factor solutions
• The varimax criterion for analytic rotation in factor analysis
• Non-symmetrical composite-based path modeling
• Handbook of partial least squares. Concepts, methods and applications.
• Comparing generalised maximum entropy and partial least squares methods for structural equation models
• Regression Quantiles
• Latent Variable Models with Fixed Effects
• Latent Variable Models for Longitudinal Data with Multiple Continuous Outcomes
• Robustness of partial least-squares method for estimating latent variable quality structures
• Using the Hybrid Two-Step estimation approach for the identification of second-order latent variable models
• Assessment and Validation in Quantile Composite-Based Path Modeling

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