fista.LpS: A function to solve low rank plus sparse model estimation...

View source: R/Functions_LpS.R

fista.LpSR Documentation

A function to solve low rank plus sparse model estimation using FISTA algorithm

Description

A function to solve low rank plus sparse model estimation

Usage

fista.LpS(
  A,
  b,
  lambda,
  mu,
  alpha_L = 0.25,
  niter = 100,
  backtracking = TRUE,
  x.true
)

Arguments

A

A design matrix with size of n by p

b

A matrix, (or vector) with size of n by p (or n by 1)

lambda

A positive numeric value, indicating the tuning parameter for sparse component

mu

A positive numeric value, indicating the tuning parameter for low rank component

alpha_L

The constraint coefficient of low rank component, default is 0.25

niter

The maximum number of iterations required for FISTA

backtracking

A boolean argument, indicating that use backtracking in the FISTA

x.true

A p by p matrix, the true model parameter. Only available for simulation.

Value

A list object, including the followings

sparse.comp

Estimated sparse component

lr.comp

Estimated low-rank component

obj.val

Values of objective function

rel.err

Relative errors compared with the true model parameters if available


VARDetect documentation built on June 22, 2024, 10 a.m.