Package: scpi 2.2.6
scpi: Prediction Intervals for Synthetic Control Methods with Multiple Treated Units and Staggered Adoption
Implementation of prediction and inference procedures for Synthetic Control methods using least square, lasso, ridge, or simplex-type constraints. Uncertainty is quantified with prediction intervals as developed in Cattaneo, Feng, and Titiunik (2021) <https://nppackages.github.io/references/Cattaneo-Feng-Titiunik_2021_JASA.pdf> for a single treated unit and in Cattaneo, Feng, Palomba, and Titiunik (2023) <doi:10.48550/arXiv.2210.05026> for multiple treated units and staggered adoption. More details about the software implementation can be found in Cattaneo, Feng, Palomba, and Titiunik (2024) <doi:10.48550/arXiv.2202.05984>.
Authors:
scpi_2.2.6.tar.gz
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scpi.pdf |scpi.html✨
scpi/json (API)
# Install 'scpi' in R: |
install.packages('scpi', repos = c('https://filippopalomba.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/nppackages/scpi/issues
- scpi_germany - Replication Dataset for Estimating the Economic Impact of German Reunification
Last updated 12 days agofrom:dbf426434a. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 12 2024 |
R-4.5-win | OK | Nov 12 2024 |
R-4.5-linux | OK | Nov 12 2024 |
R-4.4-win | OK | Nov 12 2024 |
R-4.4-mac | OK | Nov 12 2024 |
R-4.3-win | OK | Nov 12 2024 |
R-4.3-mac | OK | Nov 12 2024 |
Exports:scdatascdataMultiscestscpiscplotscplotMulti
Dependencies:abindbitbit64bootclicodetoolscolorspaceconquercpp11cubatureCVXRdata.tabledoSNOWdplyrdrECOSolveRfansifarverfastDummiesforeachFormulagenericsggplot2glmxgluegmpgtablegtoolsisobanditeratorsKernSmoothlabelinglatticelifecyclelmtestmagrittrMASSMatrixMatrixModelsmatrixStatsmgcvmunsellmvtnormnlmenpnumDerivosqppillarpkgconfigplyrpurrrQtoolsquadprogquantdrquantregR6RColorBrewerRcppRcppArmadilloRcppEigenreshape2rlangRmpfrsandwichscalesscssnowSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithrzoo