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

Documentation for package ‘model4you’ version 0.9-4

Help Pages

.add_modelinfo	Add model information to a personalised-model-ctree
.modelfit	Fit function when model object is given
.prepare_args	Prepare input for ctree/cforest from input of pmtree/pmforest
binomial_glm_plot	Plot for a given logistic regression model (glm with binomial family) with one binary covariate.
coef.pmtree	Methods for pmtree
coxph_plot	Survival plot for a given coxph model with one binary covariate.
gettree.pmforest	Compute model-based forest from model.
lm_plot	Density plot for a given lm model with one binary covariate.
logLik.pmodel_identity	Objective function of personalised models
logLik.pmtree	Extract log-Likelihood
node_pmterminal	Panel-Generator for Visualization of pmtrees
objfun	Objective function
objfun.glm	Objective function
objfun.lm	Objective function
objfun.pmodel_identity	Objective function of personalised models
objfun.pmtree	Objective function of a given pmtree
objfun.survreg	Objective function
one_factor	Check if model has only one factor covariate.
plot.heterogeneity_test	Test if personalised models improve upon base model.
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
print.summary.pmtree	Methods for pmtree
rss	Residual sum of squares
rss.default	Residual sum of squares
summary.pmtree	Methods for pmtree
survreg_plot	Survival plot for a given survreg model with one binary covariate.
varimp.pmforest	Variable Importance for pmforest