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.

Version: 3.2
Depends: methods, modelObj, stats
Imports: kernlab, rgenoud, dfoptim
Suggests: MASS, rpart, nnet
Published: 2018-02-12
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
CRAN checks: DynTxRegime results


Reference manual: DynTxRegime.pdf
Package source: DynTxRegime_3.2.tar.gz
Windows binaries: r-devel: DynTxRegime_3.2.zip, r-release: DynTxRegime_3.2.zip, r-oldrel: DynTxRegime_3.2.zip
OS X El Capitan binaries: r-release: DynTxRegime_3.2.tgz
OS X Mavericks binaries: r-oldrel: DynTxRegime_3.01.tgz
Old sources: DynTxRegime archive


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