Extract Information From a Fitted PLSR or PCR Model
Jackknife approximate t tests of regression coefficients
Plot Regression Coefficients of PLSR and PCR models
CPPLS (Indahl et al.)
Delete intercept from model matrix
NIR measurements and oil types of mayonnaise
Multiplicative Scatter Correction
Generate segments for cross-validation
Kernel PLS (Dayal and MacGregor)
Octane numbers and NIR spectra of gasoline
Partial Least Squares and Principal Component Regression
Cross-validation
Sensory and physico-chemical data of olive oils
Summary and Print Methods for PLSR and PCR objects
Extract Scores and Loadings from PLSR and PCR Models
Suggestions for the optimal number of components in PCR and PLSR models
MSEP, RMSEP and R2 of PLSR and PCR models
Plot Method for MVR objects
NIR spectra and density measurements of PET yarns
Adjust for Missing Values
Principal Component Regression
Sijmen de Jong's SIMPLS
Validation Plots
Standardization of Data Matrices
Orthogonal scores PLSR
Prediction Plots
Jackknife Variance Estimates of Regression Coefficients
Plots of Scores, Loadings and Correlation Loadings
Calculate Variance-Covariance Matrix for a Fitted Model Object
Partial Least Squares and Principal Component Regression
Set or return options for the pls package
Predict Method for PLSR and PCR
Wide Kernel PLS (Rännar et al.)
Biplots of PLSR and PCR Models.
Cross-validation of PLSR and PCR models