ACF: Auto-Covariance and Correlation Functions

In schoi355/gmwm: Generalized Method of Wavelet Moments

Auto-Covariance and Correlation Functions

Description

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

Usage

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

Arguments

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)

Details

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.

Value

An array of dimensions N x S x S.

Examples

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

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

schoi355/gmwm documentation built on April 11, 2022, 1:21 a.m.