MSCMT: Multivariate Synthetic Control Method Using Time Series (original) (raw)
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>.
| Version: | 1.4.0 |
|---|---|
| Depends: | R (≥ 3.2.0) |
| Imports: | stats, utils, parallel, lpSolve, ggplot2, lpSolveAPI, Rglpk, Rdpack |
| Suggests: | Synth, DEoptim, rgenoud, DEoptimR, GenSA, GA, soma, cmaes, Rmalschains, NMOF, nloptr, pso, LowRankQP, kernlab, reshape, knitr, rmarkdown |
| Published: | 2024-03-19 |
| DOI: | 10.32614/CRAN.package.MSCMT |
| Author: | Martin Becker  [aut, cre], 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 at mx.uni-saarland.de> |
| License: | GPL-2 | GPL-3 [expanded from: GPL] |
| Copyright: | inst/COPYRIGHTS MSCMT copyright details |
| NeedsCompilation: | yes |
| Materials: | |
| CRAN checks: | MSCMT results |
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