Package: DTRlearn2
Title: Statistical Learning Methods for Optimizing Dynamic Treatment
        Regimes
Version: 2.0
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,WeightSVM (>= 1.7-11), R
        (>= 2.10)
License: GPL-2
Encoding: UTF-8
RoxygenNote: 7.1.0
Repository: https://ychen178.r-universe.dev
Date/Publication: 2022-07-17 21:25:16 UTC
RemoteUrl: https://github.com/ychen178/dtrlearn2
RemoteRef: HEAD
RemoteSha: 5a873a1484a6ea3f1a3a8aec335e37f2c4dfa29d
NeedsCompilation: no
Packaged: 2026-06-22 10:06:58 UTC; root