nbsurv
Conditional Naive Bayes Survival Modelling for Right-Censored Data
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.5.1 |
rolling linux/jammy R-4.5 | nbsurv_0.5.1.tar.gz |
234.5 KiB |
0.5.1 |
rolling linux/noble R-4.5 | nbsurv_0.5.1.tar.gz |
234.4 KiB |
0.5.1 |
rolling source/ R- | nbsurv_0.5.1.tar.gz |
169.3 KiB |
0.5.1 |
latest linux/jammy R-4.5 | nbsurv_0.5.1.tar.gz |
234.5 KiB |
0.5.1 |
latest linux/noble R-4.5 | nbsurv_0.5.1.tar.gz |
234.4 KiB |
0.5.1 |
latest source/ R- | nbsurv_0.5.1.tar.gz |
169.3 KiB |
0.5.1 |
2026-04-23 source/ R- | nbsurv_0.5.1.tar.gz |
0 B |