| biplot.mvr | Biplots of PLSR and PCR Models. |
| coef.mvr | 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 |
| delete.intercept | Delete intercept from model matrix |
| fac2seg | Factor to Segments |
| gasoline | Octane numbers and NIR spectra of gasoline |
| jack.test | Jackknife approximate t tests of regression coefficients |
| kernelpls.fit | Kernel PLS (Dayal and MacGregor) |
| mayonnaise | NIR measurements and oil types of mayonnaise |
| msc | Multiplicative Scatter Correction |
| mvr | Partial Least Squares and Principal Component Regression |
| mvrCv | Cross-validation |
| mvrVal | MSEP, RMSEP and R2 of PLSR and PCR models |
| naExcludeMvr | Adjust for Missing Values |
| oliveoil | Sensory and physico-chemical data of olive oils |
| oscorespls.fit | Orthogonal scores PLSR |
| plot.mvr | Plot Method for MVR objects |
| pls | Partial Least Squares and Principal Component Regression |
| pls.options | Set or return options for the pls package |
| predict.mvr | Predict Method for PLSR and PCR |
| predplot | Prediction Plots |
| scoreplot | Plots of Scores, Loadings and Correlation Loadings |
| scores | Extract Scores and Loadings from PLSR and PCR Models |
| selectNcomp | Suggestions for the optimal number of components in PCR and... |
| simpls.fit | Sijmen de Jong's SIMPLS |
| stdize | Standardization of Data Matrices |
| summary.mvr | Summary and Print Methods for PLSR and PCR objects |
| svdpc.fit | Principal Component Regression |
| validationplot | Validation Plots |
| var.jack | Jackknife Variance Estimates of Regression Coefficients |
| vcov.mvr | Calculate Variance-Covariance Matrix for a Fitted Model... |
| widekernelpls.fit | Wide Kernel PLS (Rännar et al.) |
| yarn | NIR spectra and density measurements of PET yarns |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.