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 (2022) <doi:10.48550/arXiv.2202.05984>.

Version:	2.2.5
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), 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:	2023-11-01
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
In views:	CausalInference
CRAN checks:	scpi results

Documentation:

Reference manual:

scpi.pdf

Downloads:

Package source:	scpi_2.2.5.tar.gz
Windows binaries:	r-devel: scpi_2.2.5.zip, r-release: scpi_2.2.5.zip, r-oldrel: scpi_2.2.5.zip
macOS binaries:	r-release (arm64): scpi_2.2.5.tgz, r-oldrel (arm64): scpi_2.2.5.tgz, r-release (x86_64): scpi_2.2.5.tgz, r-oldrel (x86_64): scpi_2.2.5.tgz
Old sources:	scpi archive

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