VARFIMA.est: Maximum likelihood estimation of a VARFIMA(1,1) in final...

In LongMemoryTS: Long Memory Time Series

Description

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

Usage

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

Arguments

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.

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

Example output

 [1]  0.435433230  0.341547112  0.212797848 -0.159389811 -0.001650801
 [6]  0.024227781 -0.100089750  0.991749915  1.002907206  0.432771068

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