CetaFGN: Covariance Matrix of Eta for Fractional Gaussian Noise

In longmemo: Statistics for Long-Memory Processes (Book Jan Beran), and Related Functionality

Covariance Matrix of Eta for Fractional Gaussian Noise

Description

Covariance matrix of \hat{\eta} for fractional Gaussian noise (fGn).

Usage

CetaFGN(eta, m = 10000, delta = 1e-9)

Arguments

eta	parameter vector eta = c(H, *).
m	integer specifying the length of the Riemann sum, with step size 2 * pi/m. The default (10000) is realistic.
delta	step size for numerical derivative computation.

Details

Currently, the step size for numerical derivative is the same in all coordinate directions of eta. In principle, this can be far from optimal.

Value

Variance-covariance matrix of the estimated parameter vector \hat{\eta}.

Author(s)

Jan Beran (principal) and Martin Maechler (speedup, fine tuning)

See Also

specFGN

Examples

 (C.7  <- CetaFGN(0.7, m = 256))
 (C.5  <- CetaFGN(eta = c(H = 0.5), m = 256))
 (C.5. <- CetaFGN(eta = c(H = 0.5), m = 1024))

longmemo documentation built on Sept. 11, 2024, 5:18 p.m.