acf(bats)R Documentation

Autocovariance function Estimation

Description

The function acf computes estimates of the autocovariance function.

The generic function plot has a method for acf objects.

Usage

acf(x, lag.max=NULL, plot=FALSE, type=c("correlation", 
	"covariance", "partial"))
plot.acf(acf.obj, ci, ...)

Details

For type = "correlation" and "covariance", the estimates are based on the sample covariance.

The partial correlation coefficient is estimated by fitting autoregressive models of successively higher orders up to lag.max. The function ar.yw is called to do this.

Value

An object of class acf, which is a list with the following elements:
lag A three dimensional array containing the lags at which the acf is estimated.
acf An array with the same dimensions as lag containing the estimated acf.
type The type of correlation (same as the type argument).
n.used The number of observations in the time series.
series The name of the series
snames The series names for multivariate time series.

Note

The confidence interval plotted in plot.acf is based on an uncorrelated series and should be treated with appropriate caution.

Author(s)

Paul Gilbert, Martyn Plummer

See Also

ar.yw


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