Partial least squares path modeling is a statistical method that allows to analyze complex dependence relationships among several blocks of observed variables, each one represented by a latent variable. The computation of latent variable scores is an essential step of the method, achieved through an iterative procedure named here Hanafi–Wold’s procedure. The present paper generalizes properties already known in the literature for this procedure, from which additional convergence results will be obtained.

中文翻译：

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偏最小二乘路径建模中Hanafi-Wold过程的广义性质

偏最小二乘路径建模是一种统计方法，可以分析观察变量的几个块之间的复杂依存关系，每个块都由一个潜在变量表示。潜在变量分数的计算是该方法的重要步骤，通过一个称为Hanafi-Wold过程的迭代过程来实现。本文概括了此过程中文献中已知的属性，将从中获得更多的收敛结果。