mulspe {timsac}R Documentation

Multiple Spectrum

Description

Compute multiple spectrum estimates using Akaike window or Hanning window.

Usage

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

Arguments

y a multivariate time series with d variables and n observations. (y[n,d])
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 values 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: Pahse spectrums.
plot.scale logical. IF TRUE the common range of the y-axisis is used.

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". Lower triangular parts: Real parts. Upper triangular parts: 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(0,1000,2)
  x[,1] <- sgnl[4:1003]
  x[,2] <- 0.9*sgnl[1:1000]+0.2*rnorm(1000)  #x[i,2]=0.9*x[i-3,1]+0.2*N(0,1)
  mulspe(x, 100, window="Hanning", plot=TRUE, plot.scale=TRUE)

[Package timsac version 1.2.1 Index]