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funest (version 0.0.1.3)

Functional Ensemble Survival Tree for Dynamic Prediction

Description

A fast implementation of functional ensemble survival tree is provided to facilitate dynamic prediction with right-censored data. Multiple time-varying covariates can be accommodated via multivariate principal component analysis. These extracted features along with baseline covariates are nested within the ensemble survival tree where dynamic prediction can be done under user-specified sliding windows. Prediction accuracy measures, Area under the receiver operating characteristic (ROC) curve and Brier score, are provided in this package.

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Install

install.packages('funest')

Monthly Downloads

1

Version

0.0.1.3

License

GPL-3

Maintainer

Yijun Xie

Last Published

March 9th, 2020

Functions in funest (0.0.1.3)

funest_fit

Fitting functional ensemble survival tree model
predictor_loader

predictor_loader
surv_train

A sample of short form of training data
funest_pred

Predicting survival probability with time-varing covariates
surv_test

A sample of short form of testing data
long_test

A sample of long form of testing data
long_train

A sample of long form of training data