Results 301 to 310 of about 880,930 (320)
Some of the next articles are maybe not open access.
Shrinkage Structure of Partial Least Squares
Scandinavian Journal of Statistics, 2000Partial least squares regression (PLS) is one method to estimate parameters in a linear model when predictor variables are nearly collinear. One way to characterize PLS is in terms of the scaling (shrinkage or expansion) along each eigenvector of the predictor correlation matrix. This characterization is useful in providing a link between PLS and other
Lingjærde, Ole C., Christophersen, Nils
openaire +2 more sources
Partial Least Squares Path Modeling: Updated Guidelines
2017Partial least squares (PLS) path modeling is a variance-based structural equation modeling technique that is widely applied in business and social sciences. It is the method of choice if a structural equation model contains both factors and composites. This chapter aggregates new insights and offers a fresh look at PLS path modeling.
Henseler, Jörg +2 more
openaire +1 more source
2015
Partial least squares (PLS) path modeling is a variance-based form of structural equation modeling. It is frequently applied in business and social sciences to analyze complex causal-predictive models involving latent variables. PLS path modeling makes only soft assumptions with respect to the data distribution, and is relatively robust in case of ...
openaire +1 more source
Partial least squares (PLS) path modeling is a variance-based form of structural equation modeling. It is frequently applied in business and social sciences to analyze complex causal-predictive models involving latent variables. PLS path modeling makes only soft assumptions with respect to the data distribution, and is relatively robust in case of ...
openaire +1 more source
Partial Least Squares Strukturgleichungsmodellierung
2017Joseph F. Hair +5 more
openaire +1 more source