Package: shrinkDSM 0.2.0

Daniel Winkler
shrinkDSM: Efficient Bayesian Inference for Dynamic Survival Models with Shrinkage
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>.
Authors:
shrinkDSM_0.2.0.tar.gz
shrinkDSM_0.2.0.tar.gz(r-4.5-noble)shrinkDSM_0.2.0.tar.gz(r-4.4-noble)
shrinkDSM_0.2.0.tgz(r-4.4-emscripten)shrinkDSM_0.2.0.tgz(r-4.3-emscripten)
shrinkDSM.pdf |shrinkDSM.html✨
shrinkDSM/json (API)
# Install 'shrinkDSM' in R: |
install.packages('shrinkDSM', repos = 'https://cloud.r-project.org') |
- gastric - Survival times of gastric cancer patients
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 2 years agofrom:73de37c7a9. Checks:1 OK, 2 NOTE. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 22 2025 |
R-4.5-linux-x86_64 | NOTE | Mar 22 2025 |
R-4.4-linux-x86_64 | NOTE | Mar 22 2025 |
Exports:divisionpointsprep_tvinputshrinkDSM
Dependencies:codaGIGrvglatticeRcppRcppArmadilloRcppGSLRcppProgressshrinkTVPstochvolzoo
Citation
To cite package ‘shrinkDSM’ in publications use:
Winkler D, Knaus P (2022). shrinkDSM: Efficient Bayesian Inference for Dynamic Survival Models with Shrinkage. R package version 0.2.0, https://CRAN.R-project.org/package=shrinkDSM.
Corresponding BibTeX entry:
@Manual{, title = {shrinkDSM: Efficient Bayesian Inference for Dynamic Survival Models with Shrinkage}, author = {Daniel Winkler and Peter Knaus}, year = {2022}, note = {R package version 0.2.0}, url = {https://CRAN.R-project.org/package=shrinkDSM}, }