alphaOutlier (version 1.2.0)

aout.gandh: Find $\alpha$-outliers in data from the family of $g$-and-$h$ distributions

Description

Given the parameters of a $g$-and-$h$ distribution, aout.gandh identifies $\alpha$-outliers in a given data set.

Usage

aout.gandh(data, param, alpha = 0.1, hide.outliers = FALSE)

Arguments

data

a vector. The data set to be examined.

param

a vector. Contains the parameters of the $g$-and-$h$ distribution: median, scale, $g$, $h$.

alpha

an atomic vector. Determines the maximum amount of probability mass the outlier region may contain. Defaults to 0.1.

hide.outliers

boolean. Returns the outlier-free data if set to TRUE. Defaults to FALSE.

Value

is.outlier that flags the outliers with TRUE. If hide.outliers is set to TRUE, a simple vector of the outlier-free data.

Details

The concept of $\alpha$-outliers is based on the p.d.f. of the random variable. Since for $g$-and-$h$ distributions this does not exist in closed form, the computation of the outlier region is based on an optimization of the quantile function with side conditions.

References

Xu, Y.; Iglewicz, B.; Chervoneva, I. (2014) Robust estimation of the parameters of g-and-h distributions, with applications to outlier detection. Computational Statistics and Data Analysis 75, 66-80.

Examples

durations <- faithful$eruptions
aout.gandh(durations, c(4.25, 1.14, 0.05, 0.05), alpha = 0.1)