astsa (version 1.14)

acfm: ACF and CCF for Multiple Time Series

Description

Produces a grid of plots of the sample ACF (diagonal) and CCF (off-diagonal).

Usage

acfm(series, max.lag = NULL,  na.action = na.pass, ylim = NULL,
      acf.highlight = TRUE, ...)

Arguments

series

Multiple time series (at least 2 columns of time series)

max.lag

Maximum lag. Can be omitted. Defaults to \(\sqrt{n} + 10\) unless \(n < 60\). If the series is seasonal, this will be at least 4 seasons by default.

na.action

How to handle missing data; default is na.pass

ylim

Specify limits for the all correlation axes. If NULL (default) the values are a little wider than the min and max of all values.

acf.highlight

If TRUE (default), the diagonals (ACFs) are highlighted.

...

Additional arguments passed to tsplot

Details

Produces a grid of plots of the sample ACF (diagonal) and CCF (off-diagonal). The plots in the grid are estimates of corr{x(t+LAG), y(t)}. Thus x leads y if LAG is positive and x lags y if LAG is negative.

References

You can find demonstrations of astsa capabilities at FUN WITH ASTSA.

The most recent version of the package can be found at https://github.com/nickpoison/astsa/.

In addition, the News and ChangeLog files are at https://github.com/nickpoison/astsa/blob/master/NEWS.md.

The webpages for the texts are https://www.stat.pitt.edu/stoffer/tsa4/ and https://www.stat.pitt.edu/stoffer/tsda/.

Examples

# NOT RUN {
acfm(diff(log(econ5)))

acfm(diff(log(econ5)), gg=TRUE, acf=FALSE)
# }