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causaloptim
View on CRAN: Click
here
Download and install causaloptim package within the R console
Install from CRAN:
install.packages("causaloptim")
Install from Github:
library("remotes")
install_github("cran/causaloptim")
Install by package version:
library("remotes")
install_version("causaloptim", "1.0.0")
Attach the package and use:
library("causaloptim")
Maintained by
Michael C Sachs
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2020-03-20
Latest Update: 2023-10-31
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) 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 Sj
How to cite:
Michael C Sachs (2020). causaloptim: An Interface to Specify Causal Graphs and Compute Bounds on Causal Effects. R package version 1.0.0, https://cran.r-project.org/web/packages/causaloptim. Accessed 03 Dec. 2024.
Previous versions and publish date:
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imports, suggests or enhances
Complete documentation for causaloptim
Functions, R codes and Examples using
the causaloptim R package
Some associated functions: analyze_graph . causaloptim-package . causalproblemcheck . constraintscheck . create_R_matrix . create_effect_vector . create_q_matrix . create_response_function . get_default_effect . graphrescheck . interpret_bounds . latex_bounds . opt_effect . optimize_effect . optimize_effect_2 . parse_constraints . parse_effect . plot.linearcausalproblem . plot_graphres . print.linearcausalproblem . querycheck . simulate_bounds . specify_graph . update_effect .
Some associated R codes: causaloptim-package.R . graph-utilities.R . process-optimizer.R . response-functional.R . run-app.R . text-parsing.R . translation-modules.R . update-effect.R . utils.R . zzz.R . Full causaloptim package functions and examples
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