prox.sparse.func: Proximal function with l1-norm penalty updating

In LSVAR: Estimation of Low Rank Plus Sparse Structured Vector Auto-Regressive (VAR) Model

Description

Proximal function with l1-norm

Usage

prox.sparse.func(w1, y, A, b, L, lambda, AtA, Atb)

Arguments

w1	previously updated model parameter
y	updated model parameter
A	design matrix
b	correspond vector, or matrix
L	learning rate
lambda	tuning parameter for sparse component
AtA	Gram matrix of design matrix A
Atb	inner product of design matrix A and correspond vector b

Value

Value of proximal function with l1-norm penalty

LSVAR documentation built on May 26, 2021, 5:07 p.m.