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nbsurv  

Conditional Naive Bayes Survival Modelling for Right-Censored Data
View on CRAN: Click here


Download and install nbsurv package within the R console
Install from CRAN:
install.packages("nbsurv")

Install from Github:
library("remotes")
install_github("cran/nbsurv")

Install by package version:
library("remotes")
install_version("nbsurv", "0.5.1")



Attach the package and use:
library("nbsurv")
Maintained by
Imad El Badisy
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2026-09-11
Latest Update: 2026-09-11
Description:
Fits conditional naive Bayes survival models for right-censored outcomes using inverse-probability of censoring weighting. The package provides model fitting, prediction, resampling-based evaluation, cross-validation, hyper-parameter tuning, and permutation variable importance utilities for horizon-specific survival prediction. The model is the censored naive Bayes classifier of Wolfson et al. (2015) <doi:10.1002/sim.6526>, which combines the marginal Kaplan-Meier survivor function with horizon-specific class-conditional covariate densities and inverse-probability-of-censoring weights. Resampling evaluation uses the inverse-probability-of-censoring-weighted Brier score of Gerds and Schumacher (2006) <doi:10.1002/bimj.200610301>.
How to cite:
Imad El Badisy (2026). nbsurv: Conditional Naive Bayes Survival Modelling for Right-Censored Data. R package version 0.5.1, https://cran.r-project.org/web/packages/nbsurv. Accessed 24 Oct. 2026.
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