mulspe {timsac} | R Documentation |
Compute multiple spectrum estimates using Akaike window or Hanning window.
mulspe(y, lag=NULL, window="Akaike", plot=TRUE, plot.scale=FALSE)
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. |
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
spec |
spectrum smoothing by "window". Lower triangular parts: Real parts. Upper triangular parts: Imaginary parts. |
stat |
test statistics. |
coh |
simple coherence by "window". |
H.Akaike and T.Nakagawa (1988) Statistical Analysis and Control of Dynamic Systems. Kluwer Academic publishers.
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)