Package: causaloptim
Encoding: UTF-8
Type: Package
Title: An Interface to Specify Causal Graphs and Compute Bounds on
        Causal Effects
Version: 1.0.3
Date: 2026-07-01
Authors@R: c(
    person("Michael C", "Sachs", role = c("aut", "cre"), email = "sachsmc@gmail.com"), 
    person("Erin E", "Gabriel", role = "aut"), 
    person("Arvid", "Sjölander", role = "aut"), 
    person("Gustav", "Jonzon", role = "aut"),
    person("Alexander A", "Balke", role = "ctb",comment ="(C++ code)"), 
    person("Colorado", "Reed", role = "ctb", comment = "(graph-creator.js)"), 
    person("Markham", "Alex", role = "ctb", comment = "Pruning vignette")
    )
Maintainer: Michael C Sachs <sachsmc@gmail.com>
Description: When causal quantities are not identifiable from the
        observed data, it still may be possible to bound these
        quantities using the observed data. We outline a class of
        problems for which the derivation of tight bounds is always a
        linear programming problem and can therefore, at least
        theoretically, be solved using a symbolic linear optimizer. We
        extend and generalize the approach of Balke and Pearl (1994)
        <doi:10.1016/B978-1-55860-332-5.50011-0> and we provide a user
        friendly graphical interface for setting up such problems via
        directed acyclic graphs (DAG), which only allow for problems
        within this class to be depicted. The user can then define
        linear constraints to further refine their assumptions to meet
        their specific problem, and then specify a causal query using a
        text interface. The program converts this user defined DAG,
        query, and constraints, and returns tight bounds. The bounds
        can be converted to R functions to evaluate them for specific
        datasets, and to latex code for publication. The methods and
        proofs of tightness and validity of the bounds are described in
        a paper by Sachs, Jonzon, Gabriel, and Sjölander (2022)
        <doi:10.1080/10618600.2022.2071905>.
License: MIT + file LICENSE
Imports: shiny, rcdd
Depends: R (>= 4.1.0), igraph
RoxygenNote: 7.3.2
Suggests: testthat (>= 3.0.0), knitr, rmarkdown
VignetteBuilder: knitr
URL: https://sachsmc.github.io/causaloptim/
BugReports: https://github.com/sachsmc/causaloptim/issues/
Config/testthat/edition: 3
Config/pak/sysreqs: cmake libglpk-dev libgmp3-dev make libuv1-dev
        libxml2-dev zlib1g-dev
Repository: https://sachsmc.r-universe.dev
Date/Publication: 2026-07-01 07:00:36 UTC
RemoteUrl: https://github.com/sachsmc/causaloptim
RemoteRef: HEAD
RemoteSha: 2da4422fa0b62e76a70ecea6565d3e04b676dce9
NeedsCompilation: no
Packaged: 2026-07-01 10:57:54 UTC; root
Author: Michael C Sachs [aut, cre],
  Erin E Gabriel [aut],
  Arvid Sjölander [aut],
  Gustav Jonzon [aut],
  Alexander A Balke [ctb] ((C++ code)),
  Colorado Reed [ctb] ((graph-creator.js)),
  Markham Alex [ctb] (Pruning vignette)