Degrees of Freedom and Statistical Inference for Partial Least Squares Regression

benchmark.pls | Comparison of model selection criteria for Partial Least... |

benchmark.regression | Comparison of Partial Least Squares Regression, Principal... |

coef.plsdof | Regression coefficients |

compute.lower.bound | Lower bound for the Degrees of Freedom |

dA | Derivative of normalization function |

dnormalize | Derivative of normalization function |

dvvtz | First derivative of the projection operator |

first.local.minimum | Index of the first local minimum. |

information.criteria | Information criteria |

kernel.pls.fit | Kernel Partial Least Squares Fit |

krylov | Krylov sequence |

linear.pls.fit | Linear Partial Least Squares Fit |

normalize | Normalization of vectors |

pcr | Principal Components Regression |

pcr.cv | Model selection for Princinpal Components regression based on... |

pls.cv | Model selection for Partial Least Squares based on... |

pls.dof | Computation of the Degrees of Freedom |

plsdof-package | Degrees of Freedom and Statistical Inference for Partial... |

pls.ic | Model selection for Partial Least Squares based on... |

pls.model | Partial Least Squares |

ridge.cv | Ridge Regression. |

tr | Trace of a matrix |

vcov.plsdof | Variance-covariance matrix |

vvtz | Projectin operator |

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