mcnnm_lam_range: This function computes the minimum value of lambda_L which...

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

Description

This function computes the minimum value of lambda_L which causes L to be zero. User can get the output of this function and fit the low-rank model with her desired value of lambda_L.

Usage

mcnnm_lam_range(M, mask, to_estimate_u = 1L, to_estimate_v = 1L,
  niter = 1000L, rel_tol = 1e-05)

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.
to_estimate_u	Optional boolean input for wheter estimating fixed unit effects (row means of M) or not. Default is 1.
niter	Optional parameter on the number of iterations taken in the algorithm for each fixed value of lambda_L. The default value is 1000 and it is sufficiently large as the algorithm is using warm-start strategy.
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-5.
to_estimate_u	Optional boolean input for wheter estimating fixed time effects (column means of M) or not. Default is 1.

Value

The minimum value of lambda_L causing L to be zero.

Examples

mcnnm_lam_range(M = replicate(5,rnorm(5)), mask = matrix(rbinom(5*5,1,0.8),5,5))

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