Efficient Bayesian Inference for Dynamic Survival Models with Shrinkage R package shrinkDSM version 1.0.2 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>. Software 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) Daniel Winkler <daniel.winkler@unsw.edu.au> Comprehensive R Archive Network (CRAN) Daniel Winkler [aut, cre], Peter Knaus [aut] (ORCID: <https://orcid.org/0000-0001-6498-7084>) GPL (>= 2) 2026-03-24 application/tgz https://CRAN.R-project.org/package=shrinkDSM doi:10.32614/CRAN.package.shrinkDSM