Acf {forecast} | R Documentation |
The function Acf
computes (and by default plots) an estimate of the autocorrelation function of a univariate time series. Function Pacf
computes (and by default plots) an estimate of the partial autocorrelation function of a univariate time series. These improve the acf
and pacf
functions when applied to univariate time series.
The main differences are that Acf
does not plot a spike at lag 0 (which is redundant)
and the horizontal axes show lags in time units rather than seasonal units.
Acf(x, lag.max=NULL, type=c("correlation", "partial"), plot=TRUE, main=NULL, ylim=NULL, na.action=na.contiguous, ...) Pacf(x, main=NULL, ...)
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 " |
plot |
logical. If TRUE (the default) the acf is plotted. |
main |
Title for plot |
ylim |
The y limits of the plot |
na.action |
function to handle missing values. Default is |
... |
Additional arguments passed to |
See the acf
function in the stats package.
See the acf
function in the stats package.
Rob J Hyndman
Acf(wineind) Pacf(wineind)