Winkler, Daniel, Knaus, Peter. 2021. shrinkDSM: Efficient Bayesian Inference for Dynamic Survival Models with Shrinkage.
BibTeX
Abstract
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>.
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| Status of publication | Published |
|---|---|
| Affiliation | WU |
| Type of publication | Software |
| Title | shrinkDSM: Efficient Bayesian Inference for Dynamic Survival Models with Shrinkage |
| Date | Sept. 6, 2021 |
| Version | 0.1.0 |
| Licence | GPL-3 |
| Programming language | R, C++ |
Associations
- People
- Winkler, Daniel (Details)
- Knaus, Peter (Details)
- Organization
- Institute for Statistics and Mathematics IN (Details)
- Institute for Retailing & Data Science IN (Details)
- Research areas (ÖSTAT Classification 'Statistik Austria')
- 1105 Computer software (Details)
- 5323 Econometrics (Details)
- 5701 Applied statistics (Details)