fftcor {timsac} | R Documentation |
Compute auto and/or cross covariances and correlations via FFT.
fftcor(y, lag=NULL, isw=4, plot=TRUE, lag_axis=TRUE)
y |
data of channel X and Y (data of channel Y is given for isw=2 or 4 only). |
lag |
maximum lag. Default is 2*sqrt(n), where n is the length of the time series y. |
isw |
numerical flag giving the type of computation.
isw = 1 : autocorrelation of X (one-channel) isw = 2 : autocorrelations of X and Y (two-channel) isw = 4 : auto- and cross- correlations of X and Y (two-channel) |
plot |
logical. If TRUE (default) crosscorrelations are plotted. |
lag_axis |
logical. If TRUE (default) with plot=TRUE, x_axis is drawn. |
acov |
autocovariance. |
ccov12 |
crosscovariance. |
ccov21 |
crosscovariance. |
acor |
autocorrelation. |
ccor12 |
crosscorrelation. |
ccor21 |
crosscorrelation. |
mean |
mean. |
H.Akaike and T.Nakagawa (1988) Statistical Analysis and Control of Dynamic Systems. Kluwer Academic publishers.
# Example 1 x <- rnorm(200) y <- rnorm(200) xy <- array(c(x,y), dim=c(200,2)) fftcor(xy, lag_axis=FALSE) # Example 2 xorg <- rnorm(1003) x <- matrix(0,1000,2) x[,1] <- xorg[1:1000] x[,2] <- xorg[4:1003]+0.5*rnorm(1000) fftcor(x, lag=20)