This package is considered a duplicate. The official version of this package is found at:https://yo5uke.r-universe.dev/coresynth

Package: coresynth 1.0.1

Yosuke Abe

coresynth: Fast and Unified Synthetic Control Methods

A unified 'Formula' interface to the Synthetic Control Method (SCM) and related panel-data causal inference estimators: Synthetic Difference-in-Differences (SDID), Generalized Synthetic Control (GSC), Matrix Completion (MC), Time-Aware Synthetic Control (TASC), and Synthetic Interventions (SI), together with an experimental-design variant. Computational bottlenecks (quadratic programming, singular value decomposition, and Kalman filtering) are implemented in 'C++' via 'RcppArmadillo'. Methods are described in Abadie, Diamond and Hainmueller (2010) <doi:10.1198/jasa.2009.ap08746>, Arkhangelsky, Athey, Hirshberg, Imbens and Wager (2021) <doi:10.1257/aer.20190159>, Xu (2017) <doi:10.1017/pan.2016.2>, Athey, Bayati, Doudchenko, Imbens and Khosravi (2021) <doi:10.1080/01621459.2021.1891924>, and Agarwal, Shah and Shen (2025) <doi:10.1287/opre.2025.1590>.

Authors:Yosuke Abe [aut, cre]

coresynth_1.0.1.tar.gz
coresynth_1.0.1.zip(r-4.7-x86_64)coresynth_1.0.1.zip(r-4.7-arm64)coresynth_1.0.1.zip(r-4.6-x86_64)coresynth_1.0.1.zip(r-4.6-arm64)
coresynth_1.0.1.tar.gz(r-4.7-arm64)coresynth_1.0.1.tar.gz(r-4.7-x86_64)coresynth_1.0.1.tar.gz(r-4.6-arm64)coresynth_1.0.1.tar.gz(r-4.6-x86_64)
coresynth_1.0.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
coresynth/json (API)

# Install 'coresynth' in R:

install.packages('coresynth', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/yo5uke/coresynth/issues

Pkgdown/docs site:https://yo5uke.com

Uses libs:

openblas– Optimized BLAS
c++– GNU Standard C++ Library v3
openmp– GCC OpenMP (GOMP) support library

On CRAN:

openblas cpp openmp

3.75 score 1 stars 9 scripts 1.4k downloads 34 exports 35 dependencies

Last updated from:9ad5134206. Checks:10 OK. Indexed: no.

Target	Result	Time
linux-devel-arm64	OK	212
linux-devel-x86_64	OK	251
source / vignettes	OK	310
linux-release-arm64	OK	208
linux-release-x86_64	OK	223
windows-devel-arm64	OK	390
windows-devel-x86_64	OK	311
windows-release-arm64	OK	365
windows-release-x86_64	OK	189
wasm-release	OK	159

Exports:augment_scm conformal_inference donor_outcomes export_json gsc_boot gsc_ife_cpp gsc_inference kalman_smoother_cpp loo_donors mspe_ratio_pval placebo_in_time plot_data pred scm_balance_frontier scm_design scm_fit scm_inference scm_inner_weights_cpp scm_placebo_cpp scm_placebo_x_cpp scm_rank_pval scm_weights_cpp sdid_estimate_cpp sdid_inference sdid_placebo_cpp sdid_time_weights_cpp sdid_unit_weights_cpp si_inference si_pcr_cpp soft_impute_cpp soft_impute_fe_cpp synthetic_outcomes tensor_unfold_cpp treated_outcomes

Dependencies:backports broom cli cpp11 dplyr farver Formula generics ggplot2 glue gtable isoband jsonlite labeling lifecycle magrittr pillar pkgconfig purrr R6 RColorBrewer Rcpp RcppArmadillo rlang S7 scales stringi stringr tibble tidyr tidyselect utf8 vctrs viridisLite withr

Get started with coresynth

Rendered fromcoresynth.Rmdusingknitr::rmarkdown

Last update: 2026-10-11
Started: 2026-06-12

Help page	Topics
Augmented Synthetic Control Method (Ridge ASCM)	augment_scm
Conformal Inference for Synthetic Control Estimators	conformal_inference
Export coresynth Results to JSON	export_json
Glance at an inference result	glance.coresynth_inference
Parametric Bootstrap Inference for GSC (Xu 2017 S.3)	gsc_boot
Fast Interactive Fixed Effects (IFE) for Generalized Synthetic Control	gsc_ife_cpp
Non-parametric Inference for GSC (Xu 2017)	gsc_inference
Kalman Filter and RTS Smoother (TASC)	kalman_smoother_cpp
Leave-One-Out Donor Robustness for SCM	loo_donors
Permutation Inference via MSPE Ratio for SCM	mspe_ratio_pval
In-Time Placebo (Backdating) Test for SCM	placebo_in_time
Extract the tidy data behind a coresynth plot	plot_data plot_data.coresynth plot_data.default plot_data.scm_placebo
Plot a coresynth model	plot.coresynth
Plot an scm_design object	plot.scm_design
Plot a Balance Possibility Frontier	plot.scm_frontier
Plot SCM In-Space Placebo Results	plot.scm_placebo
Predictor Specification for SCM	pred
Balance Possibility Frontier for Staggered SCM	scm_balance_frontier
Experimental Synthetic Control Design	scm_design
Fit a Synthetic Control Method Model	scm_fit
Inference for Staggered SCM	scm_inference
SCM Inner Weights (QP Given V)	scm_inner_weights_cpp
Fast Leave-One-Out Placebo Test for SCM (Abadie et al. 2010)	scm_placebo_cpp
Fast Leave-One-Out Placebo Test for SCM with a Predictor Specification	scm_placebo_x_cpp
Rank-Based Permutation Test for Several Treated Units	scm_rank_pval
SCM Outer Weights (Joint Optimization of W and V)	scm_weights_cpp
Calculate SDID Estimate (tau_sdid)	sdid_estimate_cpp
Inference for Synthetic Difference-in-Differences	sdid_inference
Fast Placebo Test for SDID	sdid_placebo_cpp
Calculate SDID Time Weights (lambda)	sdid_time_weights_cpp
Calculate SDID Unit Weights (omega)	sdid_unit_weights_cpp
Non-parametric Inference for SI (Agarwal et al. 2025)	si_inference
SI-PCR: Synthetic Interventions via Principal Component Regression	si_pcr_cpp
Fast Matrix Completion using Soft-Impute Algorithm	soft_impute_cpp
Matrix Completion with Optional Two-Way Fixed Effects	soft_impute_fe_cpp
Tensor Unfolding (Matricization) for Synthetic Interventions	tensor_unfold_cpp
Tidy an inference result	tidy.coresynth_inference
Extract Outcome Series from a coresynth Fit	donor_outcomes donor_outcomes.coresynth donor_outcomes.coresynth_gsc donor_outcomes.coresynth_mc donor_outcomes.coresynth_scm donor_outcomes.coresynth_sdid donor_outcomes.coresynth_si donor_outcomes.coresynth_tasc synthetic_outcomes synthetic_outcomes.coresynth synthetic_outcomes.coresynth_staggered synthetic_outcomes.coresynth_tasc treated_outcomes treated_outcomes.coresynth

Package: coresynth 1.0.1

coresynth: Fast and Unified Synthetic Control Methods

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