active_set_1: Determine the active set variables via lasso regression.

In Marga8/HDGCvar: Granger Causality Testing in High Dimensional Vector Autoregressive Models

Determine the active set variables via lasso regression.

Description

Determine the active set variables via lasso regression.

Usage

active_set_1(i, d, p, X_index, y, z, z_a = NULL, bound = 0.5 * NROW(z))

Arguments

i	determines which column of y is considered
d	the decided lag-augmentation of the interest variables
p	the lag length
X_index	index of the Granger causing variables
y	vector/matrix of dependent variable
z	vector/matrix of regressors
z_a	those variables that should not be penalized
bound	upper bound on tuning parameter lambda

Value

the active set estimated via lasso using BIC as penalty

Marga8/HDGCvar documentation built on May 25, 2024, 11:12 a.m.