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.
- Version0.2.0
- R versionunknown
- LicenseGPL-2
- LicenseGPL-3
- Needs compilation?Yes
- Last release11/15/2022
Team
Daniel Winkler
Peter Knaus
Insights
Last 30 days
This package has been downloaded 154 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 3 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 2,447 times in the last 365 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The day with the most downloads was Sep 11, 2024 with 30 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports4 packages
- Suggests1 package
- Linking To5 packages