# Fast and Unified Synthetic Control Methods

## Documentation for package ‘coresynth’ version 0.2.0

- DESCRIPTION file
- User guides, package vignettes and other documentation
- Package NEWS
- Package README

## Help Pages

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 §3)
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