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: | 4.3 |
Depends: | methods, modelObj, stats |
Imports: | kernlab, rgenoud, dfoptim |
Suggests: | MASS, rpart, nnet |
Published: | 2019-12-13 |
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_4.3.tar.gz |
Windows binaries: | r-devel: DynTxRegime_4.3.zip, r-devel-gcc8: DynTxRegime_4.3.zip, r-release: DynTxRegime_4.3.zip, r-oldrel: DynTxRegime_4.3.zip |
OS X binaries: | r-release: DynTxRegime_4.3.tgz, r-oldrel: DynTxRegime_4.3.tgz |
Old sources: | DynTxRegime archive |
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