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DTRlearn2

1.1

Statistical Learning Methods for Optimizing Dynamic Treatment Regimes

1packages depend
21.2Kdownloads / year
test coverage
11/13checks pass

Overview

About
Maintained by Yuan ChenFirst published 2019-01-032 releasesCRAN page ↗

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.

Install

Health

CRAN checks
2NOTE11OK
Failing flavors
  • NOTE r-devel-linux-x86_64-debian-clang
  • NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 2.1 min · r-oldrel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
100%
Documentation · exports
5
Dependencies · direct
Check history
  • NOTE2026-03-10
    12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesNopkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
50%

Downloads

21.2K
CRAN downloads in the past year
Rank #2,583 · ~58/day · ~1.8K/mo
Daily download trend is not available in this view yet.
2.4K30 days
7.3K90 days
21.2K1 year
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Dependencies

Declared dependencies
3 external dependencies (excludes base and recommended)
Depends (6)
R >= 2.10kernlabMASSMatrixforeachglmnet
Imports (0)
none
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
1direct
0indirect

Code & Tests

Datasets

People & History

People (0)

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Listed in earlier versions (4)
no longer listed · 1.0 to 1.1
no longer listed · 1.0 to 1.1
no longer listed · 1.0 to 1.1
no longer listed · 1.0 to 1.1
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • R
    R 4.2.0 released · 2022-04-22
  • R
    R 4.1.0 released · 2021-05-18
  • R
    R 4.0.0 released · 2020-04-24
  • 1.1Latest
    2020-04-22 · current release · diff ↗
  • R
    R 3.6.0 released · 2019-04-26
  • 1.0
    2019-01-03
  • R
    R 3.5.0 released · 2018-04-23

Package metadata

First published
2019-01-03
Total releases
2 / 7 yrs
License
GPL-2 OSI
Minimum R
≥ 2.10
Bundled data
2.5 KB / 1 file
Download size
19 KB
Installed size
not tracked yet
With dependencies
not tracked yet
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("DTRlearn2")

Cite the R Observatory

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APA

Balamuta, J. J. (2026). R Observatory: Metrics for DTRlearn2 version 1.1 [Data set]. HJJB, LLC. Data release v2026-08-15. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-15, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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