Reference

All functions
biplot(<mvr>)	Biplots of PLSR and PCR Models.
coef(<mvr>) fitted(<mvr>) residuals(<mvr>) model.matrix(<mvr>) model.frame(<mvr>) prednames() respnames() compnames() explvar()	Extract Information From a Fitted PLSR or PCR Model
coefplot()	Plot Regression Coefficients of PLSR and PCR models
cppls.fit()	CPPLS (Indahl et al.)
crossval()	Cross-validation of PLSR and PCR models
cvsegments()	Generate segments for cross-validation
gasoline	Octane numbers and NIR spectra of gasoline
jack.test() print(<jacktest>)	Jackknife approximate t tests of regression coefficients
kernelpls.fit()	Kernel PLS (Dayal and MacGregor)
mayonnaise	NIR measurements and oil types of mayonnaise
msc() predict(<msc>) makepredictcall(<msc>)	Multiplicative Scatter Correction
mvr() plsr() cppls() pcr()	Partial Least Squares and Principal Component Regression
mvrCv()	Cross-validation
MSEP() RMSEP() R2() mvrValstats()	MSEP, RMSEP and R2 of PLSR and PCR models
oliveoil	Sensory and physico-chemical data of olive oils
oscorespls.fit()	Orthogonal scores PLSR
plot(<mvr>)	Plot Method for MVR objects
pls.options()	Set or return options for the pls package
predict(<mvr>)	Predict Method for PLSR and PCR
predplot() predplotXy()	Prediction Plots
scoreplot() plot(<scores>) loadingplot() plot(<loadings>) corrplot()	Plots of Scores, Loadings and Correlation Loadings
scores() loadings() loading.weights() Yscores() Yloadings()	Extract Scores and Loadings from PLSR and PCR Models
selectNcomp()	Suggestions for the optimal number of components in PCR and PLSR models
simpls.fit()	Sijmen de Jong's SIMPLS
stdize() predict(<stdized>) makepredictcall(<stdized>)	Standardization of Data Matrices
summary(<mvr>) print(<mvr>) print(<mvrVal>)	Summary and Print Methods for PLSR and PCR objects
svdpc.fit()	Principal Component Regression
validationplot() plot(<mvrVal>)	Validation Plots
var.jack()	Jackknife Variance Estimates of Regression Coefficients
widekernelpls.fit()	Wide Kernel PLS (Rännar et al.)
yarn	NIR spectra and density measurements of PET yarns