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) <doi:10.1080/01621459.2021.1979561> for a single treated unit and in Cattaneo, Feng, Palomba, and Titiunik (2025) <doi:10.1162/rest_a_01588> for multiple treated units and staggered adoption. More details about the software implementation can be found in Cattaneo, Feng, Palomba, and Titiunik (2025) <doi:10.18637/jss.v113.i01>.
| Version: | 3.0.1 |
| Depends: | R (≥ 4.1.0) |
| Imports: | abind (≥ 1.4.5),CVXR (≥ 1.0-10),doSNOW (≥ 1.0.19),dplyr (≥ 1.0.7),ECOSolveR (≥ 0.5.4),fastDummies (≥ 1.6.3),foreach (≥ 1.5.1),ggplot2 (≥ 3.3.3),magrittr (≥ 2.0.1),MASS (≥ 7.3),Matrix (≥ 1.3.3), methods (≥ 4.1.0), parallel (≥ 4.1.0),purrr (≥ 0.3.4),Qtools (≥ 1.5.6),reshape2 (≥1.4.4),Rdpack (≥ 2.4),rlang (≥ 0.4.11), stats (≥ 4.1.0),stringr (≥ 1.4.0),tibble (≥ 3.1.2),tidyr (≥ 1.1.3), utils (≥ 4.1.1) |
| Suggests: | testthat (≥ 3.0.0) |
| Published: | 2025-07-03 |
| DOI: | 10.32614/CRAN.package.scpi |
| Author: | Matias Cattaneo [aut], Yingjie Feng [aut], Filippo Palomba [aut, cre], Rocio Titiunik [aut] |
| Maintainer: | Filippo Palomba <fpalomba at princeton.edu> |
| License: | GPL-2 |
| URL: | https://nppackages.github.io/scpi/ |
| NeedsCompilation: | no |
| Citation: | scpi citation info |
| In views: | CausalInference |
| CRAN checks: | scpi results |
| Reference manual: | scpi.html ,scpi.pdf |
| Package source: | scpi_3.0.1.tar.gz |
| Windows binaries: | r-devel:scpi_3.0.1.zip, r-release:scpi_3.0.1.zip, r-oldrel:scpi_3.0.1.zip |
| macOS binaries: | r-release (arm64):scpi_3.0.1.tgz, r-oldrel (arm64):scpi_3.0.1.tgz, r-release (x86_64):scpi_3.0.1.tgz, r-oldrel (x86_64):scpi_3.0.1.tgz |
| Old sources: | scpi archive |
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