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LTRCforests
View on CRAN: Click
here
Download and install LTRCforests package within the R console
Install from CRAN:
install.packages("LTRCforests")
Install from Github:
library("remotes")
install_github("cran/LTRCforests")
Install by package version:
library("remotes")
install_version("LTRCforests", "0.7.0")
Attach the package and use:
library("LTRCforests")
Maintained by
Weichi Yao
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
First Published: 2020-07-03
Latest Update: 2023-11-30
Description:
Implements the conditional inference forest and relative risk 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. (2022) .
How to cite:
Weichi Yao (2020). LTRCforests: Ensemble Methods for Survival Data with Time-Varying Covariates. R package version 0.7.0, https://cran.r-project.org/web/packages/LTRCforests. Accessed 01 May. 2025.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for LTRCforests
Functions, R codes and Examples using
the LTRCforests R package
Some associated functions: LTRCforests-package . ltrccif . ltrcrrf . pbcsample . predictProb . print . sbrier_ltrc . tune.ltrccif . tune.ltrcrrf .
Some associated R codes: LTRCforests-package.R . LTRCforests.news.R . data.R . data.utilities.R . distance.R . factor.utilities.R . generic.impute.ltrcrfsrc.R . generic.predict.ltrcrfsrc.R . impute.ltrcrfsrc.R . ltrccif.R . ltrcrfsrc.R . ltrcrfsrc.fast.R . ltrcrrf.R . predict.ltrcrfsrc.R . predictProb.R . print.R . sbrier_ltrc.R . tune.ltrccif.R . tune.ltrcrrf.R . utilities.R . Full LTRCforests package functions and examples
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