ACF {wv}R Documentation

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×SN \times 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 10log10(N/m)10*log10(N/m) where NN is the number of observations and mm 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×S×SN \times S \times S.

Author(s)

Yunxiang Zhang

Examples

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

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

[Package wv version 0.1.2 Index]