Generalized Partially Linear Tree-Based Regression Model

bag.aucoob | AUC on the Out Of Bag samples |

bagging.pltr | bagging pltr models |

best.tree.BIC.AIC | Prunning the Maximal tree |

best.tree.bootstrap | parametric bootstrap on a pltr model |

best.tree.CV | Prunning the Maximal tree |

best.tree.permute | permutation test on a pltr model |

burn | burn dataset |

data_pltr | gpltr data example |

GPLTR-package | Fit a generalized partially linear tree-based regression... |

nested.trees | compute the nested trees |

pltr.glm | Partially tree-based regression model function |

predict_bagg.pltr | prediction on new features |

predict_pltr | prediction |

p.val.tree | Compute the p-value |

tree2glm | tree to GLM |

tree2indicators | From a tree to indicators (or dummy variables) |

VIMPBAG | score of importance for variables |

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