Random Forest with Multivariate Longitudinal Predictors


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Documentation for package ‘DynForest’ version 1.1.0

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compute_gVIMP Compute the grouped importance of variables (gVIMP) statistic
compute_OOBerror Compute the Out-Of-Bag error (OOB error)
compute_VIMP Compute the importance of variables (VIMP) statistic
data_simu1 data_simu1 dataset
data_simu2 data_simu1 dataset
DynForest Random forest with multivariate longitudinal endogenous covariates
pbc2 pbc2 dataset
plot.DynForest Plot results about the most predictive variables used in DynForest
plot.DynForestgVIMP Plot results about the most predictive variables used in DynForest
plot.DynForestVarDepth Plot results about the most predictive variables used in DynForest
plot.DynForestVIMP Plot results about the most predictive variables used in DynForest
plot_CIF Plot the individual Cumulative Incidence Function (CIF) for the interest cause
predict.DynForest Prediction using dynamic random forests
summary.DynForest Display the summary of DynForest
var_depth Extract characteristics from the trees building process