(Partial) Autocorrelation Function Estimation
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
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, ...)
- a univariate time series
- 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.
- character string giving the type of acf to be computed. Allowed values are "
correlation" (the default) or "
- logical. If TRUE (the default) the acf is plotted.
- Title for plot
- The y limits of the plot
- function to handle missing values. Default is
na.contiguous. Useful alternatives are
- Additional arguments passed to
acf function in the stats package.
- See the
acffunction in the stats package.