Description Usage Arguments Details Value Note Author(s) References Examples

Given the parameters of a *g*-and-*h* distribution, `aout.gandh`

identifies *α*-outliers in a given data set.

1 | ```
aout.gandh(data, param, alpha = 0.1, hide.outliers = FALSE)
``` |

`data` |
a vector. The data set to be examined. |

`param` |
a vector. Contains the parameters of the |

`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 |

The concept of *α*-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.

Data frame of the input data and an index named `is.outlier`

that flags the outliers with `TRUE`

. If hide.outliers is set to `TRUE`

, a simple vector of the outlier-free data.

Makes use of `solnp`

.

A. Rehage

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.

1 2 | ```
durations <- faithful$eruptions
aout.gandh(durations, c(4.25, 1.14, 0.05, 0.05), alpha = 0.1)
``` |

alphaOutlier documentation built on May 30, 2017, 8:11 a.m.

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