Stratified and Personalised Models Based on Model-Based Trees and Forests

binomial_glm_plot | Plot for a given logistic regression model (glm with binomial... |

coeftable.survreg | Table of coefficients for survreg model |

coxph_plot | Survival plot for a given coxph model with one binary... |

dot-add_modelinfo | Add model information to a personalised-model-ctree |

dot-modelfit | Fit function when model object is given |

dot-prepare_args | Prepare input for ctree/cforest from input of pmtree/pmforest |

lm_plot | Density plot for a given lm model with one binary covariate. |

logLik.pmtree | Extract log-Likelihood |

node_pmterminal | Panel-Generator for Visualization of pmtrees |

objfun | Objective function |

objfun.pmodel_identity | Objective function of personalised models |

objfun.pmtree | Objective function of a given pmtree |

one_factor | Check if model has only one factor covariate. |

pmforest | Compute model-based forest from model. |

pmodel | Personalised model |

pmtest | Test if personalised models improve upon base model. |

pmtree | Compute model-based tree from model. |

predict.pmtree | pmtree predictions |

print.pmtree | Methods for pmtree |

rss | Residual sum of squares |

survreg_plot | Survival plot for a given survreg model with one binary... |

varimp.pmforest | Variable Importance for pmforest |

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