fftcor: Auto And/Or Cross Correlations via FFT

In timsac: Time Series Analysis and Control Package

Auto And/Or Cross Correlations via FFT

Description

Compute auto and/or cross covariances and correlations via FFT.

Usage

  fftcor(y, lag = NULL, isw = 4, plot = TRUE, lag_axis = TRUE)

Arguments

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. 1 : auto-correlation of X (one-channel) 2 : auto-correlations of X and Y (two-channel) 4 : auto- and cross- correlations of X and Y (two-channel)
plot	logical. If TRUE (default), cross-correlations are plotted.
lag_axis	logical. If TRUE (default) with plot=TRUE, x-axis is drawn.

Value

acov	auto-covariance.
ccov12	cross-covariance.
ccov21	cross-covariance.
acor	auto-correlation.
ccor12	cross-correlation.
ccor21	cross-correlation.
mean	mean.

References

H.Akaike and T.Nakagawa (1988) Statistical Analysis and Control of Dynamic Systems. Kluwer Academic publishers.

Examples

# 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, nrow = 1000, ncol = 2)
x[, 1] <- xorg[1:1000]
x[, 2] <- xorg[4:1003] + 0.5*rnorm(1000)
fftcor(x, lag = 20)

timsac documentation built on Sept. 30, 2023, 5:06 p.m.