Title: Partial least squares Regression for generalized linear models
Author: Frederic Bertrand <frederic.bertrand@math.unistra.fr>, Nicolas
for generalized linear models and kfold crossvalidation of such
models using various criteria. It allows for missing data in
the eXplanatory variables. Bootstrap confidence intervals

Author: Frederic Bertrand <frederic.bertrand@math.unistra.fr>, Nicolas Meyer <Nicolas.Meyer@nmeyer@unistra.fr>, Myriam Maumy-Bertrand <myriam.maumy-bertrand@math.unistra.fr>.
Description: This package provides Partial least squares Regression for generalized linear models and kfold crossvalidation of such models using various criteria. It allows for missing data in the eXplanatory variables. Bootstrap confidence intervals constructions are also available.

(weighted) generalized linear models and kfold crossvalidation
of such models using various criteria. It allows for missing
data in the eXplanatory variables. Bootstrap confidence
intervals constructions are also available.

Description: This package provides Partial least squares Regression for (weighted) generalized linear models and kfold crossvalidation of such models using various criteria. It allows for missing data in the eXplanatory variables. Bootstrap confidence intervals constructions are also available.

Description: This package provides (weighted) Partial least squares Regression for generalized linear models and repeated k-fold cross-validation of such models using various criteria. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.

Suggests: MASS, plsdof, R.rsp, chemometrics, plsdepot
Title: Partial Least Squares Regression for Generalized Linear Models
Description: Provides (weighted) Partial least squares Regression for generalized linear models and repeated k-fold cross-validation of such models using various criteria. It allows for missing data in the explanatory variables. Bootstrap confidence intervals constructions are also available.