Handbook of Partial Least Squares: Concepts, Methods and Applications
Vincenzo Esposito Vinzi, Wynne W. Chin, Jörg Henseler, Huiwen Wang
Springer Science & Business Media, Mar 10, 2010 - Mathematics - 798 pages
Partial Least Squares is a family of regression based methods designed for the an- ysis of high dimensional data in a low-structure environment. Its origin lies in the sixties, seventies and eighties of the previous century, when Herman O. A. Wold vigorously pursued the creation and construction of models and methods for the social sciences, where “soft models and soft data” were the rule rather than the exception, and where approaches strongly oriented at prediction would be of great value. Theauthorwasfortunatetowitnessthedevelopment rsthandforafewyears. Herman Wold suggested (in 1977) to write a PhD-thesis on LISREL versus PLS in the context of latent variable models, more speci cally of “the basic design”. I was invited to his research team at the Wharton School, Philadelphia, in the fall of 1977. Herman Wold also honoured me by serving on my PhD-committee as a distinguished and decisive member. The thesis was nished in 1981. While I moved into another direction (speci cation, estimation and statistical inference in the c- text of model uncertainty) PLS sprouted very fruitfully in many directions, not only as regards theoretical extensions and innovations (multilevel, nonlinear extensions et cetera) but also as regards applications, notably in chemometrics, marketing, and political sciences. The PLS regression oriented methodology became part of main stream statistical analysis, as can be gathered from references and discussions in important books and journals. See e. g. Hastie et al. (2001), or Stone and Brooks (1990),Frank and Friedman (1993),Tenenhauset al. (2005),there are manyothers.
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algorithm applied assess behavior block bootstrap brand personality brand preference CBSEM Chemometrics Chin compositional data computed conceptual construct Consumer Research correlation covariance covariance-based cross-validation customer satisfaction customer value data mining data set discriminant validity distribution empirical Esposito Vinzi evaluation exogenous factor analysis FIMIX-PLS formative indicators Fornell global impact inner model interaction J¨oreskog Journal of Marketing latent variable scores LISREL loadings loyalty LVPLS Management manifest variables Marketing Research matrix measurement model missing data missing values moderating effects multicollinearity multivariate number of indicators obtained outsourcing partial least squares path coefficients perceived value performance PLS estimates PLS model PLS path modeling PLS regression predictive procedure R-square reflective indicators relationships reliability sample scale service quality service value significant simulation specific standard statistical strategy structural equation modeling structural model sun exposure Sun protection Table techniques Tenenhaus variance vector weights Wold