Acf: (Partial) Autocorrelation Function Estimation

In ttnsdcn/forecast-package: Forecasting functions for time series

Description

Largely wrappers for the acf function in the stats package. The main difference is that Acf does not plot a spike at lag 0 (which is redundant). Pacf is included for consistency.

Usage

Acf(x, lag.max=NULL, type=c("correlation", "partial"), 
   plot=TRUE, main=NULL, ...)
Pacf(x, main=NULL, ...) 

Arguments

x	a univariate time series
lag.max	maximum lag at which to calculate the acf. Default is 10*log10(N/m) where N is the number of observations and m the number of series. Will be automatically limited to one less than the number of observations in the series.
type	character string giving the type of acf to be computed. Allowed values are "correlation" (the default) or "partial".
plot	logical. If TRUE (the default) the acf is plotted.
main	Title for plot
...	Additional arguments passed to acf.

Details

See the acf function in the stats package.

Value

See the acf function in the stats package.

Author(s)

Rob J Hyndman

See Also

acf

Examples

Acf(wineind)
Pacf(wineind)

ttnsdcn/forecast-package documentation built on June 1, 2019, 2:49 a.m.