Package: DTRlearn2
Title: Statistical Learning Methods for Optimizing Dynamic Treatment
        Regimes
Version: 1.1
Author: Yuan Chen, Ying Liu, Donglin Zeng, Yuanjia Wang
Maintainer: Yuan Chen <irene.yuan.chen@gmail.com>
Description: We provide a comprehensive software to estimate general K-stage DTRs from SMARTs with Q-learning and a variety of outcome-weighted learning methods. Penalizations are allowed for variable selection and model regularization. With the outcome-weighted learning scheme, different loss functions - SVM hinge loss, SVM ramp loss, binomial deviance loss, and L2 loss - are adopted to solve the weighted classification problem at each stage; augmentation in the outcomes is allowed to improve efficiency. The estimated DTR can be easily applied to a new sample for individualized treatment recommendations or DTR evaluation.
Depends: kernlab,MASS,Matrix,foreach,glmnet, R (>= 2.10)
License: GPL-2
Encoding: UTF-8
RoxygenNote: 7.1.0
NeedsCompilation: no
Packaged: 2020-04-22 15:21:20 UTC; YChen
Repository: CRAN
Date/Publication: 2020-04-22 15:52:05 UTC
Built: R 4.6.0; ; 2026-04-26 07:05:30 UTC; unix
