Convergence of the error in Hanafi-Wold's procedure on the PLS-PM task
Partial least squares path modeling is a statistical method that facilitates examining intricate dependence relationships among various blocks of observed variables, each characterized by a latent variable. The computation of latent variable scores is a pivotal step in this method and it is accomplished through an iterative procedure. Within this paper, we investigate and tackle convergence challenges related to Hanafi-Wold's procedure in computing components for the PLS-PM algorithm. Hanafi-Wold's procedure, as well as alternative procedure, demonstrate the property of monotone convergence when mode B is considered for all blocks combined with centroid or factorial schemes. However, the absence of proof regarding the convergence of the error towards zero in Hanafi-Wold's procedure is a limitation compared to alternative procedure, which possesses this convergence property. Therefore, this paper aims to establish the convergence of the error towards zero in Hanafi-Wold’s procedure.
Authors
- Zouhair El Hadri (ORCID: https://orcid.org/0000-0003-3140-4510)
- Abderrahim Sahli (ORCID: https://orcid.org/0000-0002-1528-4849)
- Mohamed Hanafi (ORCID: https://orcid.org/0000-0003-1898-6819)
Institutions
- Mohammed V University (MA)
- Oniris (FR)
Publication Details
- Journal
- Statistics Optimization & Information Computing
- Published
- 2025-05-17
- DOI
- https://doi.org/10.19139/soic-2310-5070-2223
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00