autoplot.acf {forecast} | R Documentation |
Produces a ggplot object of their equivelent Acf, Pacf, Ccf, taperedacf and taperedpacf functions.
If autoplot
is given an acf
or mpacf
function, then an appropriate ggplot object will be created.
## S3 method for class 'acf' autoplot(object, ci=0.95, ...) ## S3 method for class 'mpacf' autoplot(object, ...) ggAcf(x, lag.max = NULL, type = c("correlation", "covariance", "partial"), plot = TRUE, na.action = na.contiguous, demean=TRUE, ...) ggPacf(x, lag.max = NULL, plot = TRUE, na.action = na.contiguous, demean=TRUE, ...) ggCcf(x, y, lag.max=NULL, type=c("correlation","covariance"), plot=TRUE, na.action=na.contiguous, ...) ggtaperedacf(x, lag.max=NULL, type=c("correlation", "partial"), plot=TRUE, calc.ci=TRUE, level=95, nsim=100, ...) ggtaperedpacf(x, ...)
object |
Object of class “acf”. |
x |
a univariate or multivariate (not Ccf) numeric time series object or a numeric vector or matrix. |
y |
a univariate numeric time series object or a numeric vector. |
ci |
coverage probability for confidence interval. Plotting of the confidence interval is suppressed if ci is zero or negative. |
lag.max |
maximum lag at which to calculate the acf. |
type |
character string giving the type of acf to be computed. Allowed values are
" |
plot |
logical. If |
na.action |
function to handle missing values. Default is |
demean |
Should covariances be about the sample means? |
calc.ci |
If |
level |
Percentage level used for the confidence intervals. |
nsim |
The number of bootstrap samples used in estimating the confidence intervals. |
... |
Other plotting parameters to affect the plot. |
None. Function produces a ggplot graph.
Mitchell O'Hara-Wild
plot.acf
, Acf
, acf
,
taperedacf
library(ggplot2) ggAcf(wineind) wineind %>% Acf(plot=FALSE) %>% autoplot ## Not run: wineind %>% taperedacf(plot=FALSE) %>% autoplot ggtaperedacf(wineind) ggtaperedpacf(wineind) ## End(Not run) ggCcf(mdeaths, fdeaths)