# plot.ACF: Plot Auto-Covariance and Correlation Functions In SMAC-Group/simts: Time Series Simulation

## Description

The acf function computes the estimated autocovariance or autocorrelation for both univariate and multivariate cases.

## Usage

 ```1 2 3 4``` ```## S3 method for class 'ACF' plot(x, xlab = NULL, ylab = NULL, show.ci = TRUE, alpha = NULL, col_ci = NULL, transparency = NULL, main = NULL, parValue = NULL, ...) ```

## Arguments

 `x` An `"ACF"` object from `ACF`. `xlab` A `string` indicating the label of x axis, the default name is 'Lags' `ylab` A `string` indicating the label of y axis, the default name is 'ACF'. `show.ci` A `bool` indicating whether to show confidence region. `alpha` A `double` indicating the confidence interval level. Default is 0.05. `col_ci` A `string` that specifies the color of the confidence interval polygon. `transparency` A `double` between 0 and 1 indicating the transparency level of the confidence region. Default is 0.25. `main` A `string` indicating the title of the plot. Default name is "Variable name - ACF plot'. `...` Additional parameters

## Value

An `array` of dimensions N x S x S.

## Author(s)

Yunxiang Zhang, Stéphane Guerrier and Yuming Zhang

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```# Calculate the Autocorrelation m = ACF(datasets::AirPassengers) # Plot with 95% CI plot(m) # Plot with 90% CI plot(m, ci = 0.90) # Plot without 95% CI plot(m, show.ci = FALSE) # More customized CI plot(m, xlab = "my xlab", ylab = "my ylab", show.ci = TRUE, alpha = NULL, col_ci = "grey", transparency = 0.5, main = "my main") ```

SMAC-Group/simts documentation built on July 23, 2018, 1:15 a.m.