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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=scpi to link to this page.
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