VARFIMA.sim: Simulation of a VARFIMA(1,1) in final equations form.

In LongMemoryTS: Long Memory Time Series

Description

VARFIMA.sim returns a sample from a VARFIMA(1,1)-process.

Usage

VARFIMA.sim(phi, THETA, d.vec, T, Sigma, approx = 100, burnin = 100)

Arguments

phi	AR(1)-parameter.
THETA	MA(1)-matrix.
d.vec	vector of memory parameters.
T	desired sample size.
Sigma	Variance-Covariance-Matrix of the innovations.
approx	order of the AR-approximation that is supposed to be used. Default is approx=100.
burnin	length of the burnin period that is discarded. Default is burnin=100.

Details

add details here.

References

Lutkepohl, H. (2007): New introduction to multiple time series analysis. Springer.

Examples

series<-VARFIMA.sim(phi=0.4, THETA=matrix(c(0,0,0,0),2,2), 
d.vec=c(0.4,0.3), T=1000, Sigma=matrix(c(1,0.4,0.4,1),2,2))
ts.plot(series, col=1:2)
acf(series, lag=100)

LongMemoryTS documentation built on May 2, 2019, 5:58 a.m.