R: Multiple Spectrum

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.
`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.
`plot.scale` | logical. IF `TRUE`, the common range of the y-axis 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, 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", plot.scale = TRUE)

[Package timsac version 1.3.6 Index]