simOuts

simOuts generates uniform outliers in each dimension in (min- 2.range, max+ 2.range)

Provides a function to detect and trim outliers in Gaussian mixture model-based clustering using methods described in Clark and McNicholas (2024) <doi:10.1007/s00357-024-09473-3>.

Katharine M. Clark

oclust

Gaussian Model-Based Clustering with Outliers

Paul D. McNicholas

simOuts function

<dl><dt>data</dt>
<dd>The data in data frame form</dd>
<dt>alpha</dt>
<dd>The proportion of outliers to add in terms of the original data size</dd>
<dt>seed</dt>
<dd>Set the seed for reproducibility</dd></dl>

Arguments

Simulate Outliers — simOuts

<dl>

<dt>data</dt>
<dd>The data in data frame form</dd>


<dt>alpha</dt>
<dd>The proportion of outliers to add in terms of the original data size</dd>


<dt>seed</dt>
<dd>Set the seed for reproducibility</dd>

</dl>

simOuts: Simulate Outliers

Description

Usage

Value

Arguments