bandpass.var.spp: Bandpass Variance for Long-Memory Processes

In neuroconductor/waveslim: Basic Wavelet Routines for One-, Two-, and Three-Dimensional Signal Processing

Bandpass Variance for Long-Memory Processes

Description

Computes the band-pass variance for fractional difference (FD) or seasonal persistent (SP) processes using numeric integration of their spectral density function.

Usage

bandpass.fdp(a, b, d)

bandpass.spp(a, b, d, fG)

bandpass.spp2(a, b, d1, f1, d2, f2)

bandpass.var.spp(delta, fG, J, Basis, Length)

Arguments

fG, f1, f2	Gegenbauer frequency.
J	Depth of the wavelet transform.
Basis	Logical vector representing the adaptive basis.
Length	Number of elements in Basis.
a	Left-hand boundary for the definite integral.
b	Right-hand boundary for the definite integral.
d, delta, d1, d2	Fractional difference parameter.

Details

See references.

Value

Band-pass variance for the FD or SP process between a and b.

Author(s)

B. Whitcher

References

McCoy, E. J., and A. T. Walden (1996) Wavelet analysis and synthesis of stationary long-memory processes, Journal for Computational and Graphical Statistics, 5, No. 1, 26-56.

Whitcher, B. (2001) Simulating Gaussian stationary processes with unbounded spectra, Journal for Computational and Graphical Statistics, 10, No. 1, 112-134.

neuroconductor/waveslim documentation built on Feb. 6, 2023, 6:56 a.m.