Bayesian inference and cure rate modeling
Code for the paper Papastamoulis and Milienos (2023). Bayesian inference and cure rate modeling for event history data. arXiv:2310.06926
The file example.R generates synthetic data and then applies the proposed methodology.
The file Recidivism_Iowa_5000.txt contains the recidivism dataset used in our paper.
The developer version of the package is now available. Main features
- allow general number of covariates (with/out constant term)
- dedicated functions for plotting and summarizing the output.
> sessionInfo()
R version 4.2.1 (2022-06-23)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 22.04.2 LTS
Matrix products: default
BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.10.0
LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=el_GR.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=el_GR.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=el_GR.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=el_GR.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] parallel stats graphics grDevices utils datasets methods
[8] base
other attached packages:
[1] pracma_2.3.8 doParallel_1.0.17 iterators_1.0.14
[4] foreach_1.5.2 coda_0.19-4 RcppArmadillo_0.10.5.0.0
[7] Rcpp_1.0.8.3
loaded via a namespace (and not attached):
[1] compiler_4.2.1 codetools_0.2-18 grid_4.2.1 lattice_0.20-44