Package: MSCMT 1.4.4

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_1.4.4.tar.gz
MSCMT_1.4.4.zip(r-4.7-x86_64)MSCMT_1.4.4.zip(r-4.7-arm64)MSCMT_1.4.4.zip(r-4.6-x86_64)MSCMT_1.4.4.zip(r-4.6-arm64)
MSCMT_1.4.4.tar.gz(r-4.7-arm64)MSCMT_1.4.4.tar.gz(r-4.7-x86_64)MSCMT_1.4.4.tar.gz(r-4.6-arm64)MSCMT_1.4.4.tar.gz(r-4.6-x86_64)
MSCMT_1.4.4.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
MSCMT/json (API)

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

Bug tracker:https://github.com/mabe0033/mscmt/issues

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

On CRAN:

Conda:

openblasfortran

4.07 score 2 stars 49 scripts 483 downloads 1 mentions 7 exports 23 dependencies

Last updated from:3d38c48000. Checks:9 OK, 1 WARNING. Indexed: no.

TargetResultTimeFilesSyslog
linux-devel-arm64OK109
linux-devel-x86_64OK167
source / vignettesOK316
linux-release-arm64OK107
linux-release-x86_64OK137
windows-devel-arm64OK236
windows-devel-x86_64OK172
windows-release-arm64WARNING227
windows-release-x86_64OK95
wasm-releaseOK119

Exports:comparedidimproveSynthlistFromLongmscmtppratiopvalue

Dependencies:clicpp11farverggplot2gluegtableisobandlabelinglifecyclelpSolvelpSolveAPIR6rbibutilsRColorBrewerRdpackRglpkrlangS7scalesslamvctrsviridisLitewithr

Checking and Improving Results of package Synth
Introduction | First Example | Generating the result of package Synth | Checking the result | Second Example | Summary | References

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

SCM Using Time Series
Introduction | Definition of the Standard Model | Removing the Lagged Dependent Variable | SCMT without the Lagged Dependent Variable | Summary | References

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

Working with package MSCMT
Introduction | Preparing the Data | Example | Defining the Model | Single Estimation | Placebo Study | Making Use of a Cluster | Statistical Inference | Summary | References

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