Learning Algorithms for Dynamic Treatment Regimes

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.


Reference manual

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1.3 by Ying Liu, a year ago

Browse source code at https://github.com/cran/DTRlearn

Authors: Ying Liu , Yuanjia Wang , Donglin Zeng

Documentation:   PDF Manual  

GPL-2 license

Depends on kernlab, MASS, glmnet, ggplot2

See at CRAN