VARFIMA.est: Maximum likelihood estimation of a VARFIMA(1,1) in final...
In FunWithR/LongMemoryTS: Long Memory Time Series

Description Usage Arguments Details References Examples

VARFIMA.est returns the maximum likelihood estimate of the parameter vector of a VARFIMA(1,1) in final equations form.

1	VARFIMA.est(data, approx = 100, split = 1, rep = FALSE)

`data`	data matrix with T observations of q-dimensional process.
`approx`	order of the AR-approximation that is supposed to be used. Default is `approx=100`.
`split`	to increase the speed the sample can be divided in `split` parts. Parmeter estimation is then carried out seperately for each subsample and results are averaged across the subsamples.
`rep`	is passed to `ll_VARFIMA` and determines whether the current parameter vector is printed to the user in every iteration of the numerical maximization procedure.

add details here.

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

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)
VARFIMA.est(series, approx=100, rep=FALSE)