lookout (version 0.1.4)

autoplot.persistingoutliers: Plots outlier persistence for a range of significance levels.

Description

This function plots outlier persistence for a range of significance levels using the algorithm lookout, an outlier detection method that uses leave-one-out kernel density estimates and generalized Pareto distributions to find outliers.

Usage

# S3 method for persistingoutliers
autoplot(object, alpha = object$alpha, ...)

Value

A ggplot object.

Arguments

object

The output of the function `persisting_outliers`.

alpha

The significance levels to plot.

...

Other arguments currently ignored.

Examples

X <- rbind(
  data.frame(
    x = rnorm(500),
    y = rnorm(500)
  ),
  data.frame(
    x = rnorm(5, mean = 10, sd = 0.2),
    y = rnorm(5, mean = 10, sd = 0.2)
  )
)
plot(X, pch = 19)
outliers <- persisting_outliers(X, unitize = FALSE)
autoplot(outliers)