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Produces a ggplot object of their equivalent Acf, Pacf, Ccf, taperedacf and taperedpacf functions.
# S3 method for acf
autoplot(object, ci = 0.95, ...)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,
...
)
# S3 method for mpacf
autoplot(object, ...)
ggtaperedacf(
x,
lag.max = NULL,
type = c("correlation", "partial"),
plot = TRUE,
calc.ci = TRUE,
level = 95,
nsim = 100,
...
)
ggtaperedpacf(x, ...)
Object of class “acf
”.
coverage probability for confidence interval. Plotting of the confidence interval is suppressed if ci is zero or negative.
Other plotting parameters to affect the plot.
a univariate or multivariate (not Ccf) numeric time series object or a numeric vector or matrix.
maximum lag at which to calculate the acf.
character string giving the type of acf to be computed. Allowed
values are "correlation
" (the default), “covariance
” or
“partial
”.
logical. If TRUE
(the default) the resulting ACF, PACF or
CCF is plotted.
function to handle missing values. Default is
na.contiguous
. Useful alternatives are
na.pass
and na.interp
.
Should covariances be about the sample means?
a univariate numeric time series object or a numeric vector.
If TRUE
, confidence intervals for the ACF/PACF
estimates are calculated.
Percentage level used for the confidence intervals.
The number of bootstrap samples used in estimating the confidence intervals.
A ggplot object.
If autoplot
is given an acf
or mpacf
object, then an
appropriate ggplot object will be created.
ggtaperedpacf
plot.acf
, Acf
,
acf
, taperedacf
# NOT RUN {
library(ggplot2)
ggAcf(wineind)
wineind %>% Acf(plot=FALSE) %>% autoplot
# }
# NOT RUN {
wineind %>% taperedacf(plot=FALSE) %>% autoplot
ggtaperedacf(wineind)
ggtaperedpacf(wineind)
# }
# NOT RUN {
ggCcf(mdeaths, fdeaths)
# }
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