G.hat: Estimation of G matrix for multivariate long memory processes.
Description
G.hat Estimates the matrix G of a multivariate long memory process
based on an estimate of the vector of memory parameters. The assumed spectral
density is that of Shimotsu (2007).
Usage
G.hat(X, d, m)
Arguments
X
data matrix with T observations of q-dimensional process.
d
q-dimensional data vector.
m
bandwith parameter specifying the number of Fourier frequencies.
used for the estimation usually floor(1+T^delta), where 0<delta<1.
References
Shimotsu, K. (2007): Gaussian semiparametric estimation of multivariate
fractionally integrated processes. Journal of Econometrics, Vol. 137, No. 2, pp. 277 - 310.
# NOT RUN {T<-500d1<-0.4d2<-0.2data<-FI.sim(T, q=2, rho=0, d=c(d1,d2))
G.hat(X=data, d=c(d1,d2), m=floor(1+T^0.6))
#diagonal elements should equal 1/(2*pi)# }