mulspe {timsac}

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")