Partial Least Squares and Principal Component Regression

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 |

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.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 |

widekernelpls.fit | Wide Kernel PLS (R<c3><83><c2><a4>nnar et al.) |

yarn | NIR spectra and density measurements of PET yarns |

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