# plot.acf: Plot Autocovariance and Autocorrelation Functions

 plot.acf R Documentation

## 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 `"acf"`. `ci` coverage probability for confidence interval. Plotting of the confidence interval is suppressed if `ci` is zero or negative. `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 `x` indicating how many rows and columns of plots should be put on one page, using `par(mfrow = c(m,m))`. `ask` logical; if `TRUE`, the user is asked before a new page is started. `mar, oma, mgp, xpd, cex.main` graphics parameters as in `par(*)`, by default adjusted to use smaller than default margins for multivariate `x` only. `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.

`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
```