Package: MSCMT
Type: Package
Encoding: UTF-8
Version: 1.3.7
Date: 2023-04-17
Title: Multivariate Synthetic Control Method Using Time Series
Authors@R: c(person("Martin","Becker", role = c("aut","cre"),
    email = "martin.becker@mx.uni-saarland.de",
    comment=c(ORCID="0000-0003-2336-9751")),
    person("Stefan","Klößner", role = c("aut"),
    email = "S.Kloessner@mx.uni-saarland.de"),
    person("Karline","Soetaert", role = c("com"),
    email = "karline.soetaert@nioz.nl"),
    person("Jack","Dongarra",role=c("cph"),
    email = "dongarra@icl.utk.edu"),
    person("R.J.","Hanson",role=c("cph")),
    person("K.H.","Haskell",role=c("cph")),
    person("Cleve","Moler",role=c("cph")),
    person("LAPACK authors", role = "cph"))
Depends: R (>= 3.2.0)
Imports: stats, utils, parallel, lpSolve, ggplot2, lpSolveAPI, Rglpk,
        Rdpack
Suggests: DEoptim, rgenoud, DEoptimR, GenSA, GA, soma, cmaes, NMOF,
        nloptr, hydroPSO, pso, kernlab, reshape, knitr, rmarkdown
Description: Three generalizations of the synthetic control method (which has 
    already an implementation in package 'Synth') are implemented: first, 
    'MSCMT' allows for using multiple outcome variables, second, time series 
    can be supplied as economic predictors, and third, a well-defined 
    cross-validation approach can be used.
    Much effort has been taken to make the implementation as stable as possible 
    (including edge cases) without losing computational efficiency.
    A detailed description of the main algorithms is given in 
    Becker and Klößner (2018) <doi:10.1016/j.ecosta.2017.08.002>.
License: GPL
Copyright: inst/COPYRIGHTS
RoxygenNote: 7.2.3
VignetteBuilder: knitr
BuildVignettes: yes
NeedsCompilation: yes
Packaged: 2023-04-17 15:12:38 UTC; mabe003
Author: Martin Becker [aut, cre] (<https://orcid.org/0000-0003-2336-9751>),
  Stefan Klößner [aut],
  Karline Soetaert [com],
  Jack Dongarra [cph],
  R.J. Hanson [cph],
  K.H. Haskell [cph],
  Cleve Moler [cph],
  LAPACK authors [cph]
Maintainer: Martin Becker <martin.becker@mx.uni-saarland.de>
Repository: CRAN
Date/Publication: 2023-04-17 18:20:06 UTC
Built: R 4.1.3; x86_64-w64-mingw32; 2023-04-20 14:12:47 UTC; windows
Archs: i386, x64
