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: 4.1
Depends: methods, modelObj, stats
Imports: kernlab, rgenoud, dfoptim
Suggests: MASS, rpart, nnet
Published: 2019-03-21
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

Downloads:

Reference manual: DynTxRegime.pdf
Package source: DynTxRegime_4.1.tar.gz
Windows binaries: r-devel: DynTxRegime_4.0.zip, r-release: DynTxRegime_4.0.zip, r-oldrel: DynTxRegime_4.1.zip
OS X binaries: r-release: DynTxRegime_4.0.tgz, r-oldrel: DynTxRegime_4.0.tgz
Old sources: DynTxRegime archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=DynTxRegime to link to this page.