Fast and Unified Synthetic Control Methods


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Documentation for package ‘coresynth’ version 0.2.0

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augment_scm Augmented Synthetic Control Method (Ridge ASCM)
conformal_inference Conformal Inference for Synthetic Control Estimators
export_json Export coresynth Results to JSON
glance.coresynth_inference Glance at an inference result
gsc_boot Parametric Bootstrap Inference for GSC (Xu 2017 ยง3)
gsc_ife_cpp Fast Interactive Fixed Effects (IFE) for Generalized Synthetic Control
gsc_inference Non-parametric Inference for GSC (Xu 2017)
kalman_smoother_cpp Kalman Filter and RTS Smoother (TASC)
mspe_ratio_pval Permutation Inference via MSPE Ratio for SCM
plot.coresynth Plot a coresynth model
plot.scm_design Plot an scm_design object
pred Predictor Specification for SCM
scm_design Experimental Synthetic Control Design
scm_fit Fit a Synthetic Control Method Model
scm_inner_weights_cpp SCM Inner Weights (QP Given V)
scm_placebo_cpp Fast Leave-One-Out Placebo Test for SCM (Abadie et al. 2010)
scm_weights_cpp SCM Outer Weights (Joint Optimization of W and V)
sdid_estimate_cpp Calculate SDID Estimate (tau_sdid)
sdid_inference Inference for Synthetic Difference-in-Differences
sdid_placebo_cpp Fast Placebo Test for SDID
sdid_time_weights_cpp Calculate SDID Time Weights (lambda)
sdid_unit_weights_cpp Calculate SDID Unit Weights (omega)
si_inference Non-parametric Inference for SI (Agarwal et al. 2025)
si_pcr_cpp SI-PCR: Synthetic Interventions via Principal Component Regression
soft_impute_cpp Fast Matrix Completion using Soft-Impute Algorithm
tensor_unfold_cpp Tensor Unfolding (Matricization) for Synthetic Interventions
tidy.coresynth_inference Tidy an inference result