plot.PACF: Plot Partial Auto-Covariance and Correlation Functions

In simts: Time Series Analysis Tools

Plot Partial Auto-Covariance and Correlation Functions

Description

The function plots the output of the theo_pacf and auto_corr functions (partial autocovariance or autocorrelation functions).

Usage

## S3 method for class 'PACF'
plot(
  x,
  xlab = NULL,
  ylab = NULL,
  show.ci = TRUE,
  alpha = NULL,
  col_ci = NULL,
  transparency = NULL,
  main = NULL,
  parValue = NULL,
  ...
)

Arguments

x	A "PACF" object output from theo_pacf or auto_corr.
xlab	A string indicating the label of the x axis: the default name is 'Lags'.
ylab	A string indicating the label of the y axis: the default name is 'PACF'.
show.ci	A bool indicating whether to show the confidence region. Defaults to TRUE.
alpha	A double indicating the level of significance for the confidence interval. By default alpha = 0.05 which gives a 1 - alpha = 0.95 confidence interval.
col_ci	A string that specifies the color of the region covered by the confidence intervals (confidence region).
transparency	A double between 0 and 1 indicating the transparency level of the color defined in col_ci. Defaults to 0.25.
main	A string indicating the title of the plot. Default name is "Variable name PACF plot'.
parValue	A vector defining the margins for the plot.
...	Additional parameters

Author(s)

Yunxiang Zhang and Yuming Zhang

Examples

# Plot the Partial Autocorrelation
m = auto_corr(datasets::AirPassengers, pacf = TRUE)
plot(m)

# 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")

simts documentation built on Aug. 31, 2023, 5:07 p.m.