plot.acf
Plot Autocovariance and Autocorrelation Functions
Description
Plot method for objects of class "acf"
.
Usage
## S3 method for class 'acf' plot(x, ci = 0.95, type = "h", xlab = "Lag", ylab = NULL, ylim = NULL, main = NULL, ci.col = "blue", ci.type = c("white", "ma"), max.mfrow = 6, ask = Npgs > 1 && dev.interactive(), mar = if(nser > 2) c(3,2,2,0.8) else par("mar"), oma = if(nser > 2) c(1,1.2,1,1) else par("oma"), mgp = if(nser > 2) c(1.5,0.6,0) else par("mgp"), xpd = par("xpd"), cex.main = if(nser > 2) 1 else par("cex.main"), verbose = getOption("verbose"), ...)
Arguments
x | an object of class |
ci | coverage probability for confidence interval. Plotting of the confidence interval is suppressed if |
type | the type of plot to be drawn, default to histogram like vertical lines. |
xlab | the x label of the plot. |
ylab | the y label of the plot. |
ylim | numeric of length 2 giving the y limits for the plot. |
main | overall title for the plot. |
ci.col | colour to plot the confidence interval lines. |
ci.type | should the confidence limits assume a white noise input or for lag k an MA(k-1) input? Can be abbreviated. |
max.mfrow | positive integer; for multivariate |
ask | logical; if |
mar, oma, mgp, xpd, cex.main | graphics parameters as in |
verbose | logical. Should R report extra information on progress? |
... | graphics parameters to be passed to the plotting routines. |
Note
The confidence interval plotted in plot.acf
is based on an uncorrelated series and should be treated with appropriate caution. Using ci.type = "ma"
may be less potentially misleading.
See Also
acf
which calls plot.acf
by default.
Examples
require(graphics) z4 <- ts(matrix(rnorm(400), 100, 4), start = c(1961, 1), frequency = 12) z7 <- ts(matrix(rnorm(700), 100, 7), start = c(1961, 1), frequency = 12) acf(z4) acf(z7, max.mfrow = 7) # squeeze onto 1 page acf(z7) # multi-page
Copyright (©) 1999–2012 R Foundation for Statistical Computing.
Licensed under the GNU General Public License.