soft_impute_cpp: Fast Matrix Completion using Soft-Impute Algorithm

In coresynth: Fast and Unified Synthetic Control Methods

Fast Matrix Completion using Soft-Impute Algorithm

Description

Solves: min_L (1/2) ||O o (Y - L)||F^2 + lambda * ||L||* via iterative SVD soft-thresholding (Mazumder, Hastie, Tibshirani 2010). Note: lambda is NOT normalized by |O|. Default lambda = 0.01 * sigma_max(Y).

Usage

soft_impute_cpp(Y, O, lambda, max_iter = 1000L, tol = 1e-05)

Arguments

Y	Observed outcome matrix (N x T). Unobserved entries should be 0.
O	Binary mask matrix (N x T): 1 = observed, 0 = missing (treated post).
lambda	Nuclear norm penalty (soft-threshold on singular values).
max_iter	Maximum iterations.
tol	Convergence tolerance (relative Frobenius norm change).

Value

A numeric matrix of the same dimension as Y (N x T): the completed low-rank matrix L that minimises the soft-thresholded nuclear-norm objective.

coresynth documentation built on Aug. 28, 2026, 1:06 a.m.