MSCMT (1.3.4)

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Multivariate Synthetic Control Method Using Time Series.

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 Klner (2018) .

Maintainer: Martin Becker
Author(s): Martin Becker [aut, cre] (<>), Stefan Klner [aut], Karline Soetaert [com], Jack Dongarra [cph], R.J. Hanson [cph], K.H. Haskell [cph], Cleve Moler [cph], LAPACK authors [cph]

License: GPL

Uses: ggplot2, lpSolve, lpSolveAPI, Rdpack, Rglpk, DEoptim, LowRankQP, Synth, kernlab, reshape, rgenoud, cmaes, pso, soma, GenSA, nloptr, NMOF, knitr, Rmalschains, hydroPSO, GA, DEoptimR, rmarkdown

Released 4 months ago.

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