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obliqueRSF
View on CRAN: Click
here
Download and install obliqueRSF package within the R console
Install from CRAN:
install.packages("obliqueRSF")
Install from Github:
library("remotes")
install_github("cran/obliqueRSF") Install by package version:
library("remotes")
install_version("obliqueRSF", "0.1.2") Attach the package and use:
library("obliqueRSF")
Maintained by
Byron Jaeger
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2018-11-02
Latest Update: 2022-08-28
Description:
Oblique random survival forests incorporate linear combinations of input variables into random survival forests (Ishwaran, 2008 ). Regularized Cox proportional hazard models (Simon, 2016 ) are used to identify optimal linear combinations of input variables.
How to cite:
Byron Jaeger (2018). obliqueRSF: Oblique Random Forests for Right-Censored Time-to-Event Data. R package version 0.1.2, https://cran.r-project.org/web/packages/obliqueRSF. Accessed 10 Nov. 2026.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for obliqueRSF
Functions, R codes and Examples using
the obliqueRSF R package
Some associated functions: ORSF . obliqueRSF . pdplot . predict.orsf . predictSurvProb.orsf . print.orsf . theme_Publication . vdplot .
Some associated R codes: RcppExports.R . oblique_survival_forest_fit.R . oblique_survival_forest_predict.R . oblique_survival_forest_predictSurvProb.R . oblique_survival_forest_print.R . package.R . partial_dependence_plot.R . theme_Publication.R . variable_dependence_plot.R . zzz.R . Full obliqueRSF package functions and examples
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