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cff-version: 1.2.0
message: 'To cite package "nbsurv" in publications use:'
type: software
license: GPL-3.0-only
title: 'nbsurv: Conditional Naive Bayes Survival Modelling for Right-Censored Data'
version: 0.5.1
doi: 10.32614/CRAN.package.nbsurv
abstract: 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) <https://doi.org/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) <https://doi.org/10.1002/bimj.200610301>.
authors:
- family-names: El Badisy
  given-names: Imad
  email: elbadisyimad@gmail.com
repository: https://ielbadisy.r-universe.dev
repository-code: https://github.com/ielbadisy/nbsurv
commit: 5dc8f04338d75edebf494f7bf4382726716e6c94
url: https://github.com/ielbadisy/nbsurv
date-released: '2026-08-31'
contact:
- family-names: El Badisy
  given-names: Imad
  email: elbadisyimad@gmail.com