Dynamic treatment regimens (DTRs) are sequential decision rules tailored at each stage by time-varying subject-specific features and intermediate outcomes observed in previous stages. This package implements three methods: O-learning (Zhao et. al. 2012,2014), Q-learning (Murphy et. al. 2007; Zhao et.al. 2009) and P-learning (Liu et. al. 2014, 2015) to estimate the optimal DTRs.
| Version: | 1.2 |
| Depends: | kernlab, MASS, glmnet, ggplot2 |
| Published: | 2015-12-28 |
| Author: | Ying Liu, Yuanjia Wang, Donglin Zeng |
| Maintainer: | Ying Liu <yl2802 at cumc.columbia.edu> |
| License: | GPL-2 |
| NeedsCompilation: | no |
| CRAN checks: | DTRlearn results |
| Reference manual: | DTRlearn.pdf |
| Package source: | DTRlearn_1.2.tar.gz |
| Windows binaries: | r-devel: DTRlearn_1.2.zip, r-release: DTRlearn_1.2.zip, r-oldrel: DTRlearn_1.2.zip |
| OS X Mavericks binaries: | r-release: DTRlearn_1.2.tgz, r-oldrel: DTRlearn_1.2.tgz |
| Old sources: | DTRlearn archive |
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