fista_sparse {multivar}R Documentation

Estimate a Sparse Multiple-Subject Vector Autoregression (VAR) Model

Description

Function for estimating multiple-subjbect Vector Autoregression (VAR) models using Fast Iterative Shrinkage-Thresholding Algorithm (FISTA; Beck and Teboulle, 2009)

Usage

fista_sparse(A, b, lambda, x_true, niter, backtrack, w = NULL,
  conv = 1e-10)

Arguments

A

An N x P design matrix.

b

An N x P outcome matrix.

lambda

Regularization parameter.

x_true

Numeric matrix containing the true transition matrix (if available).

niter

Integer giving the maximum number of iterations.

backtrack

Logical. If backtracking should be used in the FISTA algorithm.

w

Numeric matrix containing the weights (if available).

conv

Convergance criterion.

Details

Function Under Development

This is a prototype function and is currently under development.

References

Fisher, Z.F., Kim, Y., and Pipiras, V. (Under Review) Penalized Estimation and Forecasting of Multiple Subject Intensive Longitudinal Data.

Beck A. and Teboulle, M. (2009). A Fast Iterative Shrinkage-Thresholding Algorithm for Linear Inverse Problems. SIAM J. Img. Sci. 2, 1, 183–202.

Examples


theta    <- matrix(rnorm(9),3,3)
data     <- var_sim(20, theta, diag(.1,3))
datalag  <- embed(data, 2)
b        <- datalag[,1:3]
A        <- datalag[,4:6]
fista_sparse(A, b, 1, theta, niter = 1, backtrack = TRUE)



[Package multivar version 0.0.1 Index]