bandpass: Bandpass Variance for Long-Memory Processes

In andrewzm/waveslim: Basic wavelet routines for one-, two- and three-dimensional signal processing

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

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

Details

See references.

Value

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

Author(s)

Brandon 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.

andrewzm/waveslim documentation built on May 10, 2019, 11:16 a.m.