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causalOT

1.0.4

Optimal Transport Weights for Causal Inference

0packages depend
5.1Kdownloads / year
14.6%test coverage
13/13checks pass

Overview

About
Maintained by Eric DunipaceFirst published 2022-03-147 releasesCRAN page ↗

Uses optimal transport distances to find probabilistic matching estimators for causal inference. These methods are described in Dunipace, Eric (2021) doi:10.48550/arXiv.2109.01991. The package will build the weights, estimate treatment effects, and calculate confidence intervals via the methods described in the paper. The package also supports several other methods as described in the help files.

Install

Health

CRAN checks
13OK
Slowest check: 5.4 min · r-devel-windows-x86_64
Code health
Yes
Tests · ratio 0.37
14.6%
Coverage · measured lines
100%
Documentation · exports
14
Dependencies · direct
Check history
  • OK2026-08-05
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-08-01
    12 OK · 1 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • OK2026-05-02
    13 OK · 0 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • NOTE2026-04-22
    11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-18
    10 OK · 3 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
Show 4 earlier snapshots
  • NOTE2026-04-10
    8 OK · 6 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-04-09
    7 OK · 6 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
  • NOTE2026-03-18
    11 OK · 3 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
  • ERROR2026-03-10
    5 OK · 2 NOTE · 0 WARNING · 7 ERROR · 0 FAILURE

Documentation

Documentation
READMEYes · 202 wordsVignettesYes · dynamicpkgdown siteNoNEWSYes · 100% structuredCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
100%
Return-value docs
100%
References docs
0%

Downloads

5.1K
CRAN downloads in the past year
Rank #6,088 · ~14/day · ~421/mo
Daily download trend is not available in this view yet.
29430 days
1.3K90 days
5.1K1 year
Compare downloads with other packages →
Also on447 r2u5 autocran

Dependencies

Declared dependencies
23 external dependencies (excludes base and recommended)
Depends (1)
R >= 4.1.0
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

Datasets

People & History

People (1)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Package Timeline

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

  • R
    R 4.6.0 released · 2026-04-24
  • 1.0.4Latest
    2026-03-10 · current release · diff ↗
  • 1.0.3
    2026-02-15 · diff ↗
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • 1.0.2
    2024-02-18 · diff ↗
  • 1.0.1
    2023-11-30 · diff ↗
  • 1.0
    2023-11-28 · diff ↗
  • unarchivedReturned to CRAN
    2023-11-28
  • archivedRemoved from CRAN
    2023-08-22
    requires archived package 'approxOT'
  • R
    R 4.3.0 released · 2023-04-21
  • 0.1.2
    2022-09-04 · diff ↗
  • R
    R 4.2.0 released · 2022-04-22
  • 0.1
    2022-03-14
  • R
    R 4.1.0 released · 2021-05-18

Package metadata

First published
2022-03-14
Total releases
7 / 4 yrs
License
GPL (== 3.0)
Additional repositories
ericdunipace.github.io
Minimum R
≥ 4.1.0
Bundled data
5.6 KB / 1 file
Download size
1.8 MB
Installed size
not tracked yet
With dependencies
not tracked yet

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("causalOT")
Dunipace, E. (2026). causalOT: Optimal Transport Weights for Causal Inference (Version 1.0.4) [Computer software]. https://doi.org/10.32614/CRAN.package.causalOT

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for causalOT version 1.0.4 [Data set]. HJJB, LLC. Data release v2026-08-22. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-22, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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