Package: causalOT
Type: Package
Title: Optimal Transport Weights for Causal Inference
Version: 1.0.2
Date: 2024-02-17
Author: Eric Dunipace [aut, cre] (<https://orcid.org/0000-0001-8909-213X>)
Authors@R: 
    person("Eric", "Dunipace", 
        role = c("aut", "cre"),
        email = "edunipace@mail.harvard.edu",
        comment = c(ORCID = "0000-0001-8909-213X"))
Maintainer: Eric Dunipace <edunipace@mail.harvard.edu>
Description: Uses optimal transport distances to find probabilistic 
    matching estimators for causal inference.
    These methods are described in Dunipace, Eric (2021) <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.
License: GPL (== 3.0)
Imports: CBPS, ggplot2, lbfgsb3c, loo, Matrix (>= 1.5-0), matrixStats,
        methods, osqp, R6 (>= 2.4.1), Rcpp (>= 1.0.3), rlang, sandwich,
        torch, utils
LinkingTo: BH (>= 1.66.0), Rcpp (>= 0.12.0), RcppEigen (>= 0.3.3.3.0),
        torch
Suggests: data.table (>= 1.12.8), testthat (>= 2.1.0), knitr,
        reticulate, rkeops (>= 2.2.2), rmarkdown, V8, withr
Additional_repositories: https://ericdunipace.github.io/drat/
Biarch: true
Depends: R (>= 3.5.0)
Encoding: UTF-8
RoxygenNote: 7.3.1
LazyData: true
VignetteBuilder: knitr
Collate: 'DataSimClass.R' 'dataHolder.R' 'weightsClass.R' 'ESS.R'
        'OT.R' 'PSIS.R' 'RcppExports.R' 'balanceFunctions.R'
        'barycentricProjection.R' 'calc_weight.R' 'causalOT-package.R'
        'cost_functions.R' 'scmClass.R' 'gridSearch.R' 'cotClass.R'
        'cotOOP.R' 'cot_opts.R' 'likelihoodClass.R' 'mean_balance.R'
        'summary.R' 'supportedMethods.R' 'treatment_effect.R' 'utils.R'
        'zzz.R'
NeedsCompilation: yes
Packaged: 2024-02-18 21:20:35 UTC; eifer
Repository: CRAN
Date/Publication: 2024-02-18 22:50:08 UTC
Built: R 4.3.2; x86_64-apple-darwin20; 2024-02-18 23:39:07 UTC; unix
Archs: causalOT.so.dSYM
