Algorithms for multi-group PLS

作者：Eslami Aida^*; Qannari El Mostafa; Kohler Achim; Bougeard Stephanie

来源：Journal of Chemometrics, 2014, 28(3): 192-201.

DOI：10.1002/cem.2593

• multi-group partial least squares regression
• multi-group principal components analysis
• nonlinear iterative partial least squares algorithm
• partial least squares regression

Several approaches of investigation of the relationships between two datasets where the individuals are structured into groups are discussed. These strategies fit within the framework of partial least squares (PLS) regression. Each strategy of analysis is introduced on the basis of a maximization criterion, which involves the covariances between components associated with the groups of individuals in each dataset. Thereafter, algorithms are proposed to solve these maximization problems. The strategies of analysis can be considered as extensions of multi-group principal components analysis to the context of PLS regression. Copyright (c) 2014 John Wiley %26 Sons, Ltd. Partial least squares regression is adapted to the case where the datasets are structured into groups of individuals. Several algorithms are proposed. The outcomes of the various strategies of analysis are compared on the basis of a case study.

• 出版日期2014-3