sim.var: Simulate a VAR(1) process

In fnets: Factor-Adjusted Network Estimation and Forecasting for High-Dimensional Time Series

Simulate a VAR(1) process

Description

Simulate a VAR(1) process; see the reference for the generation of the transition matrix.

Usage

sim.var(n, p, Gamma = diag(1, p), heavy = FALSE)

Arguments

n	sample size
p	dimension
Gamma	innovation covariance matrix; ignored if heavy = TRUE
heavy	if heavy = FALSE, common shocks are generated from rnorm whereas if heavy = TRUE, from rt with df = 5 and then scaled by sqrt(3 / 5)

Value

a list containing

data	ts object with n rows and p columns
A	transition matrix
Gamma	innovation covariance matrix

References

Barigozzi, M., Cho, H. & Owens, D. (2024+) FNETS: Factor-adjusted network estimation and forecasting for high-dimensional time series. Journal of Business & Economic Statistics (to appear).

Owens, D., Cho, H. & Barigozzi, M. (2024+) fnets: An R Package for Network Estimation and Forecasting via Factor-Adjusted VAR Modelling. The R Journal (to appear).

Examples

idio <- sim.var(500, 50)

fnets documentation built on May 29, 2024, 8:42 a.m.