Package: MSCMT 1.4.0

Martin Becker

MSCMT: 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 Klößner (2018) <doi:10.1016/j.ecosta.2017.08.002>.

Authors: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]

MSCMT_1.4.0.tar.gz
MSCMT_1.4.0.tar.gz(r-4.5-noble)MSCMT_1.4.0.tar.gz(r-4.4-noble)
MSCMT_1.4.0.tgz(r-4.4-emscripten)MSCMT_1.4.0.tgz(r-4.3-emscripten)
MSCMT.pdf |MSCMT.html
MSCMT/json (API)
NEWS

# Install 'MSCMT' in R:
install.packages('MSCMT', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • fortran– Runtime library for GNU Fortran applications

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

3.79 score 2 stars 34 scripts 453 downloads 1 mentions 7 exports 34 dependencies

Last updated 9 months agofrom:f937b426f4. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKNov 15 2024
R-4.5-linux-x86_64OKNov 15 2024

Exports:comparedidimproveSynthlistFromLongmscmtppratiopvalue

Dependencies:clicolorspacefansifarverggplot2gluegtableisobandlabelinglatticelifecyclelpSolvelpSolveAPImagrittrMASSMatrixmgcvmunsellnlmepillarpkgconfigR6rbibutilsRColorBrewerRdpackRglpkrlangscalesslamtibbleutf8vctrsviridisLitewithr

Checking and Improving Results of package Synth

Rendered fromCheckingSynth.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2024-03-20
Started: 2016-07-25

SCM Using Time Series

Rendered fromUsingTimeSeries.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2024-03-20
Started: 2016-07-25

Working with package MSCMT

Rendered fromWorkingWithMSCMT.Rmdusingknitr::rmarkdownon Nov 15 2024.

Last update: 2024-03-20
Started: 2016-07-25