ccf2 {astsa} | R Documentation |
Produces a nice graphic of the sample CCF of two time series. The actual CCF values are returned invisibly.
ccf2(x, y, max.lag = NULL, main = NULL, ylab = "CCF", plot = TRUE, na.action = na.pass, type = c("correlation", "covariance"), ...)
x, y |
univariate time series |
max.lag |
maximum lag for which to calculate the CCF |
main |
plot title - if NULL, uses x and y names |
ylab |
vertical axis label; default is 'CCF' |
plot |
if TRUE (default) a graphic is produced and the values are returned invisibly. Otherwise, the values are returned. |
na.action |
how to handle missing values; default is |
type |
default is cross-correlation; an option is cross-covariance |
... |
additional arguments passed to |
This will produce a graphic of the sample corr[x(t+lag), y(t)]
from -max.lag
to max.lag
. Also, the (rounded) values of the CCF are returned invisibly unless plot=FALSE
. Similar details apply to the cross-covariance.
D.S. Stoffer
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/.
ccf2(soi, rec, plot=FALSE) # now you see it ccf2(soi, rec) # now you don't # happy birthday mom ccf2(soi, rec, col=rainbow(36, v=.8), lwd=4)