Results 231 to 240 of about 176,958 (287)

Differentiation of Pueraria lobata and Pueraria thomsonii using partial least square discriminant analysis (PLS-DA)

Journal of Pharmaceutical and Biomedical Analysis, 2013
Kelvin Chan, Ka H Wong, Valentina Razmovski-Naumovski   +2 more
exaly   +2 more sources

Alternative partial least-squares (PLS) algorithms

Perspectives in Drug Discovery and Design, 1998
Mathematical treatments and modelling of large data structures have always created problems. From the infancy of computers to the late 1980s, the limiting factor when modelling large data structures was often the size of the computer memory.
Fredrik Lindgren, Stefan Rännar
openaire   +1 more source

On robust partial least squares (PLS) methods

Journal of Chemometrics, 1998
PLS regression methods have been used in applied fields for two decades. Techniques based on iteratively reweighted regression have appeared in the specialized literature with the contaminated data case. We propose a new robust PLS technique based on statistical procedures for covariance matrix robustification.
Juan A. Gil, Rosario Romera
openaire   +1 more source

Classification of Metabolites with Kernel-Partial Least Squares (K-PLS)

Drug Metabolism and Disposition, 2007
Numerous experimental and computational approaches have been developed to predict human drug metabolism. Since databases of human drug metabolism information are widely available, these can be used to train computational algorithms and generate predictive approaches. In turn, they may be used to assist in the identification of possible metabolites from
Mark J, Embrechts, Sean, Ekins
openaire   +2 more sources

Kernel Analysis of Partial Least Squares (PLS) Regression Models

Applied Spectroscopy, 2011
An analytical technique based on kernel matrix representation is demonstrated to provide further chemically meaningful insight into partial least squares (PLS) regression models. The kernel matrix condenses essential information about scores derived from PLS or principal component analysis (PCA).
Hideyuki, Shinzawa, Pitiporn, Ritthiruangdej, Yukihiro, Ozaki   +2 more
openaire   +2 more sources

Partial Least Squares Strukturgleichungsmodellierung (PLS-SEM): Eine anwendungsorientierte Einführung

2017
Die Partial Least Squares Strukturgleichungsmodellierung (PLS-SEM) hat sich in der wirtschafts- und sozialwissenschaftlichen Forschung als geeignetes Verfahren zur Schätzung von Kausalmodellen behauptet. Dank der Anwenderfreundlichkeit des Verfahrens und der vorhandenen Software ist es inzwischen auch in der Praxis etabliert.
Hair, Joseph F., Hult, G. Tomas M., Ringle, Christian M., Sarstedt, Marko, Richter, Nicole F., Hauff, Sven   +5 more
openaire   +3 more sources

A review of using partial least square structural equation modeling in e‐learning research

British Journal of Educational Technology, 2019
Partial least squares structural equation modeling (PLS-SEM) has become a key multivariate statistical modeling technique that educational researchers frequently use.
Hung-Ming Lin, Ming-Hsien Lee, Jyh‐Chong Liang, Hsin‐Yi Chang, P. Huang, Chin-Chung Tsai   +5 more
semanticscholar   +1 more source

On the use of partial least squares (PLS) and balancing for nonlinear model reduction

Proceedings of the 2005, American Control Conference, 2005., 2005
Model reduction is an important technique to reduce the complexity of nonlinear process models for controller design. The goal is to approximate the model as accurate as possible while at the same time achieve a speedup in computation time. The technique presented in this paper combines balancing with partial least squares (PLS) for achieving a small ...
Chuili Sun, Juergen Hahn
openaire   +1 more source

The Probability of Chance Correlation Using Partial Least Squares (PLS)

Quantitative Structure-Activity Relationships, 1993
AbstractThe frequency of chance correlation using partial least squares (PLS) has been measured experimentally for variously dimensioned data, comprising either completely random numbers, random numbers containing a perfect correlation within, and CoMFA field descriptors. This frequency, much lower than that for stepwise multiple regression, is maximal
Matthew Clark, Richard D. Cramer
openaire   +1 more source

Partial Least Squares (PLS): Its strengths and limitations

Perspectives in Drug Discovery and Design, 1993
For structure-activity correlation, Partial Least Squares (PLS) has many advantages over regression, including the ability to robustly handle more descriptor variables than compounds, nonorthogonal descriptors and multiple biological results, while providing more predictive accuracy and a much lower risk of chance correlation. The major limitations are
openaire   +1 more source