mulspe: Multiple Spectrum

In timsac: Time Series Analysis and Control Package

Multiple Spectrum

Description

Compute multiple spectrum estimates using Akaike window or Hanning window.

Usage

  mulspe(y, lag = NULL, window = "Akaike", plot = TRUE, ...)

Arguments

y	a multivariate time series with d variables and n observations.
lag	maximum lag. Default is 2 \sqrt{n}, where n is the number of observations.
window	character string giving the definition of smoothing window. Allowed strings are "Akaike" (default) or "Hanning".
plot	logical. If TRUE (default) spectrums are plotted as (d,d) matrix. Diagonal parts : Auto spectrums for each series. Lower triangular parts : Amplitude spectrums. Upper triangular part : Phase spectrums.
...	graphical arguments passed to plot.specmx.

Details

Hanning Window :	a1(0)=0.5,	a1(1)=a1(-1)=0.25,	a1(2)=a1(-2)=0
Akaike Window :	a2(0)=0.625,	a2(1)=a2(-1)=0.25,	a2(2)=a2(-2)=-0.0625

Value

spec	spectrum smoothing by 'window'.
specmx	spectrum matrix. An object of class "specmx". On and lower diagonal : Real parts Upper diagonal : Imaginary parts
stat	test statistics.
coh	simple coherence by 'window'.

References

H.Akaike and T.Nakagawa (1988) Statistical Analysis and Control of Dynamic Systems. Kluwer Academic publishers.

Examples

sgnl <- rnorm(1003)
x <- matrix(0, nrow = 1000, ncol = 2)
x[, 1] <- sgnl[4:1003]
# x[i,2] = 0.9*x[i-3,1] + 0.2*N(0,1)
x[, 2] <- 0.9*sgnl[1:1000] + 0.2*rnorm(1000)
mulspe(x, lag = 100, window = "Hanning")

timsac documentation built on Sept. 30, 2023, 5:06 p.m.