Partial Least Squares (PLS) Methods: Origins, Evolution, and Application to Social Sciences
نویسندگان
چکیده
منابع مشابه
Partial Least Squares Regression (PLS)
Number of latents The same number of factors will be extracted for PLS responses as for PLS factors. The researcher must specify how many latents to extract (in SPSS the default is 5). There is no one criterion for deciding how many latents to employ. Common alternatives are: 1. Cross-validating the model with increasing numbers of factors, then choosing the number with minimum prediction error...
متن کاملPartial Least Squares (PLS) Regression
Pls regression is a recent technique that generalizes and combines features from principal component analysis and multiple regression. It is particularly useful when we need to predict a set of dependent variables from a (very) large set of independent variables (i.e., predictors). It originated in the social sciences (specifically economy, Herman Wold 1966) but became popular first in chemomet...
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Simultaneous determination of difloxacin and enrofloxacin using two chemometric methods, partial least squares regression (PLS) and direct orthogonal signal correction-partial least squares regression (DOSC-PLS) is described in this paper. The simultaneous determination of these drugs is difficult due to spectral interferences. The calibration graphs were linear in the range of 1-10 μg mL-1 and...
متن کاملPartial least squares methods: partial least squares correlation and partial least square regression.
Partial least square (PLS) methods (also sometimes called projection to latent structures) relate the information present in two data tables that collect measurements on the same set of observations. PLS methods proceed by deriving latent variables which are (optimal) linear combinations of the variables of a data table. When the goal is to find the shared information between two tables, the ap...
متن کاملClassification of metabolites with kernel-partial least squares (K-PLS).
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 a large number of molecules in drug discov...
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ژورنال
عنوان ژورنال: Communications in Statistics - Theory and Methods
سال: 2011
ISSN: 0361-0926,1532-415X
DOI: 10.1080/03610921003778225