ACF: Auto-Covariance and Correlation Functions
In SMAC-Group/gmwm: Generalized Method of Wavelet Moments

Description Usage Arguments Details Value Examples

The acf function computes the estimated autocovariance or autocorrelation for both univariate and multivariate cases.

1	ACF(x, lagmax = 0, cor = TRUE, demean = TRUE)

`x`	A `matrix` with dimensions N x S or N observations and S processes
`lagmax`	A `integer` indicating the max lag.
`cor`	A `bool` indicating whether the correlation (`TRUE`) or covariance (`FALSE`) should be computed.
`demean`	A `bool` indicating whether the data should be detrended (`TRUE`) or not (`FALSE`)

lagmax default is 10*log10(N/m) where N is the number of observations and m is the number of series being compared. If lagmax supplied is greater than the number of observations, then one less than the total will be taken.

An array of dimensions N x S x S.

# Get Autocorrelation
m = ACF(datasets::AirPassengers)

# Get Autocovariance and do not remove trend from signal
m = ACF(datasets::AirPassengers, cor = FALSE, demean = FALSE)