DynTxRegime
Methods for Estimating Optimal Dynamic Treatment Regimes
Methods to estimate dynamic treatment regimes using Interactive Q-Learning, Q-Learning, weighted learning, and value-search methods based on Augmented Inverse Probability Weighted Estimators and Inverse Probability Weighted Estimators. Dynamic Treatment Regimes: Statistical Methods for Precision Medicine, Tsiatis, A. A., Davidian, M. D., Holloway, S. T., and Laber, E. B., Chapman & Hall/CRC Press, 2020, ISBN:978-1-4987-6977-8.
- Version4.15
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release11/24/2023
Documentation
Team
Shannon T. Holloway
S. T. Holloway, E. B. Laber, K. A. Linn, B. Zhang, M. Davidian, and A. A. Tsiatis
Insights
Last 30 days
Last 365 days
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
- Depends3 packages
- Imports3 packages
- Suggests3 packages
- Reverse Imports2 packages