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.
| Version: | 4.5 |
| Depends: | methods, modelObj, stats |
| Imports: | kernlab, rgenoud, dfoptim |
| Suggests: | MASS, rpart, nnet |
| Published: | 2020-06-27 |
| Author: | S. T. Holloway, E. B. Laber, K. A. Linn, B. Zhang, M. Davidian, and A. A. Tsiatis |
| Maintainer: | Shannon T. Holloway <sthollow at ncsu.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | DynTxRegime results |
| Reference manual: | DynTxRegime.pdf |
| Package source: | DynTxRegime_4.5.tar.gz |
| Windows binaries: | r-devel: DynTxRegime_4.5.zip, r-release: DynTxRegime_4.4.zip, r-oldrel: DynTxRegime_4.5.zip |
| macOS binaries: | r-release: DynTxRegime_4.5.tgz, r-oldrel: DynTxRegime_4.5.tgz |
| Old sources: | DynTxRegime archive |
| Reverse imports: | DevTreatRules |
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