qwraps2 (version 0.6.1)

qacf: Autocorrelation plot

Description

ggplot2 style autocorrelation plot

Usage

qacf(
  x,
  conf_level = 1 - getOption("qwraps2_alpha", 0.05),
  show_sig = FALSE,
  ...
)

Value

a ggplot.

Arguments

x

object

conf_level

confidence level for determining ‘significant’ correlations

show_sig

logical, highlight significant correlations

...

Other arguments passed to acf

Details

qacf calls acf to generate a data set which is then plotted via ggplot2.

More details and examples for graphics within qwraps2 are in the vignette(“qwraps2-graphics”, package = “qwraps2”)

See Also

acf.

Examples

# Generate a random data set
set.seed(42)
n <- 250
x1 <- x2 <- x3 <- x4 <- vector('numeric', length = n)
x1[1] <- runif(1)
x2[1] <- runif(1)
x3[1] <- runif(1)
x4[1] <- runif(1)

# white noise
Z_1 <- rnorm(n, 0, 1)
Z_2 <- rnorm(n, 0, 2)
Z_3 <- rnorm(n, 0, 5)

for(i in 2:n)
{
  x1[i] <- x1[i-1] + Z_1[i] - Z_1[i-1] + x4[i-1] - x2[i-1]
  x2[i] <- x2[i-1] - 2 * Z_2[i] + Z_2[i-1] - x4[i-1]
  x3[i] <- x3[i-1] + x2[i-1] + 0.2 * Z_3[i] + Z_3[i-1]
  x4[i] <- x4[i-1] + runif(1, 0.5, 1.5) * x4[i-1]
}
testdf <- data.frame(x1, x2, x3, x4)

# qacf plot for one variable
qacf(testdf$x1)
qacf(testdf$x1, show_sig = TRUE)

# more than one variable
qacf(testdf)
qacf(testdf, show_sig = TRUE)