adh_mp_rows: Computing Synthetic Control Estimator when multiple units are...

In susanathey/MCPanel: Matrix Completion algorithms for Causal Panel Data Models

Description

Computing Synthetic Control Estimator when multiple units are missing. The underlying algorithm is Mirror Descent with Entropy Regularizer. This algorithm is also known as exponentiated gradient descent. It is worth noting that this estimator was proposed by Abadie et. al and the reason of new implementation here is to compare methods on some datasets.

Usage

adh_mp_rows(M, mask, niter = 10000, rel_tol = 1e-08)

Arguments

M	Matrix of observed entries. The input should be N (number of units) by T (number of time periods).
mask	Binary mask with the same shape as M containing observed entries.
niter	Optional parameter on the number of iterations taken in the algorithm. The default value is 10000 and if the number of treated units are large for speed consideration will be reduced to 200.
rel_tol	Optional parameter on the stopping rule. Once the relative improve in objective value drops below rel_tol, execution is halted. Default value is 1e-8.

Value

The matrix with all missing entries filled.

See Also

The R package called synth, written by Alberto Abadie, Alexis Diamond, and Jens Hainmueller.

Examples

adh_mp_rows(matrix(c(1,2,3,4),2,2), matrix(c(1,1,1,0),2,2))

susanathey/MCPanel documentation built on May 29, 2019, 9:51 a.m.