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LTRCforests (version 0.5.1)

Ensemble Methods for Survival Data with Time-Varying Covariates

Description

Implements the conditional inference forest and random survival forest algorithm to modeling left-truncated right-censored data with time-invariant covariates, and (left-truncated) right-censored survival data with time-varying covariates. It also provides functions to tune the parameters and evaluate the model fit. See Yao et al. (2020) .

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Version

Install

install.packages('LTRCforests')

Monthly Downloads

48

Version

0.5.1

License

GPL (>= 2)

Maintainer

Weichi Yao

Last Published

September 20th, 2020

Functions in LTRCforests (0.5.1)

LTRCforests-package

Constructs forest methods for left-truncated and right-censored (LTRC) survival data
tune.ltrccf

Tune mtry to the optimal value with respect to out-of-bag error for a LTRCCF model
ltrcrrf

Fit a LTRC relative risk forest
ltrccf

Fit a LTRC conditional inference forest
tune.ltrcrrf

Tune mtry to the optimal value with respect to out-of-bag error for a LTRCRRF model
pbcsample

Sample Mayo Clinic Primary Biliary Cirrhosis Data
predictProb

Compute a Survival Curve from a LTRCCF model or a LTRCRRF model
print

Print Summary Output of a ltrccf object or a ltrcrrf object
sbrier_ltrc

Model fit evaluation for LTRC forests.