Description Usage Arguments Details Value Author(s) References See Also Examples
Computes the multivariate Fourier Whittle estimator of the long-run covariance matrix (also called fractal connectivity) for a given value of long-memory parameters d
.
1 | mfw_cov_eval(d, x, m)
|
d |
vector of long-memory parameters (dimension should match dimension of x) |
x |
data (matrix with time in rows and variables in columns) |
m |
truncation number used for the estimation of the periodogram |
The choice of m determines the range of frequencies used in the computation of
the periodogram, lambda_j = 2*pi*j/N, j = 1,... , m
. The optimal value depends on the spectral properties of the time series such as the presence of short range dependence. In Shimotsu (2007), m
is chosen to be equal to N^0.65.
long-run covariance matrix estimation.
S. Achard and I. Gannaz
K. Shimotsu (2007) Gaussian semiparametric estimation of multivariate fractionally integrated processes Journal of Econometrics Vol. 137, N. 2, pages 277-310.
S. Achard, I. Gannaz (2016)
Multivariate wavelet Whittle estimation in long-range dependence. Journal of Time Series Analysis, Vol 37, N. 4, pages 476-512. http://arxiv.org/abs/1412.0391
.
S. Achard, I Gannaz (2019) Wavelet-Based and Fourier-Based Multivariate Whittle Estimation: multiwave. Journal of Statistical Software, Vol 89, N. 6, pages 1-31.
1 2 3 4 5 6 7 8 9 10 11 12 13 | ### Simulation of ARFIMA(0,\code{d},0)
rho <- 0.4
cov <- matrix(c(1,rho,rho,1),2,2)
d <- c(0.4,0.2)
J <- 9
N <- 2^J
resp <- fivarma(N, d, cov_matrix=cov)
x <- resp$x
long_run_cov <- resp$long_run_cov
m <- 57 ## default value of Shimotsu
G <- mfw_cov_eval(d,x,m) # estimation of the covariance matrix when d is known
|
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