shrinkDSM: Efficient Bayesian Inference for Dynamic Survival Models withShrinkage
Efficient Markov chain Monte Carlo (MCMC) algorithms for fully Bayesian estimation of dynamic survival models with shrinkage priors. Details on the algorithms used are provided in Wagner (2011) <doi:10.1007/s11222-009-9164-5>, Bitto and Frühwirth-Schnatter (2019) <doi:10.1016/j.jeconom.2018.11.006> and Cadonna et al. (2020) <doi:10.3390/econometrics8020020>.
| Version: | 1.0.0 |
| Depends: | R (≥ 3.3.0) |
| Imports: | Rcpp,stochvol (≥ 3.0.3),coda, utils,shrinkTVP (≥ 2.0.2),survival |
| LinkingTo: | Rcpp,RcppArmadillo,RcppProgress,stochvol,shrinkTVP |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-04-11 |
| DOI: | 10.32614/CRAN.package.shrinkDSM |
| Author: | Daniel Winkler [aut, cre], Peter Knaus [aut] |
| Maintainer: | Daniel Winkler <daniel.winkler at wu.ac.at> |
| License: | GPL-2 |GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| CRAN checks: | shrinkDSM results |
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