dataVARX1: Sample data from a VARX(1) model
In ragt2ridges: Ridge Estimation of Vector Auto-Regressive (VAR) Processes

Description Usage Arguments Value Author(s) See Also Examples

Sample data from a VARX(1) model.

1	dataVARX1(X, A, B, SigmaE, lagX)

`X`	Three-dimensional `array` containing the time-varying covariates. The first, second and third dimensions correspond to covariates, time and samples, respectively. The data are assumed to be centered covariate-wise.
`A`	A `matrix` \mathbf{A} of autoregression parameters.
`B`	A `matrix` \mathbf{B} of regression parameters of the time-varying covariates stored in the array `X`.
`SigmaE`	Covariance `matrix` of the errors (innovations).
`lagX`	An `integer`, either `0` or 1, specifying whether \mathbf{X}_t or \mathbf{X}_{t-1} affects \mathbf{Y}_t, respectively.

A three dimensional array containing the data. The first, second and third dimensions correspond to covariates, time and samples, respectively.

Wessel N. van Wieringen <w.vanwieringen@vumc.nl>

createA, createS, dataVAR1, dataVAR2, ridgeVARX1.

# set dimensions (p=covariates, n=individuals, T=time points)
p <- 3; n <- 12; T <- 10

# set model parameters
SigmaE <- diag(p)/4
Ax     <- createA(3, "chain")

# generate time-varying covariate data
X <- dataVAR1(n, T, Ax, SigmaE)

# autoregression parameter matrices of VARX(1) model
A <- createA(p, topology="clique", nonzeroA=0.1, nClique=1)
B <- createA(p, topology="hub",    nonzeroA=0.1, nHubs=1)

# generate data
Y <- dataVARX1(X, A, B, SigmaE, lagX=0)