  The aim of the plsRglm package is to deal with complete and incomplete
datasets through several new techniques or, at least, some which were not yet
implemented in R. Indeed, not only does it make available the extension of the
PLS regression to the generalized linear regression models, but also bootstrap
techniques, leave-one-out and repeated $k$-fold cross-validation. In addition,
graphical displays help the user to assess the significance of the predictors
when using bootstrap techniques. Biplots (Fig. 4) can be used to delve into the
relationship between individuals and variables.
