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

plsRglm: Partial least squares linear and generalized linear regression  for processing incomplete datasets by cross-validation and bootstrap  techniques with R