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

In lookout: Leave One Out Kernel Density Estimates for Outlier Detection

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 class 'persistingoutliers'
autoplot(object, alpha = object$alpha, ...)

Arguments

object	The output of the function 'persisting_outliers'.
alpha	The significance levels to plot.
...	Other arguments currently ignored.

Value

A ggplot object.

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)

lookout documentation built on Oct. 14, 2022, 1:09 a.m.