klist

To create a <a href="/link/list?package=QuantileGH&version=0.1.8" data-mini-rdoc="QuantileGH::list">list</a> of observations based on (modified) \(k\)-means algorithm.

internal

Functions for simulation, estimation, and model selection of
finite mixtures of Tukey g-and-h distributions.

Tingting Zhan

QuantileGH

Quantile Least Mahalanobis Distance Estimator for Tukey g-&-h
Mixture

Inna Chervoneva

klist function

<dl><dt>x</dt>
<dd><a href="/link/numeric?package=QuantileGH&version=0.1.8" data-mini-rdoc="QuantileGH::numeric">numeric</a> <a href="/link/vector?package=QuantileGH&version=0.1.8" data-mini-rdoc="QuantileGH::vector">vector</a>, one-dimensional observations</dd>
<dt>K</dt>
<dd><a href="/link/integer?package=QuantileGH&version=0.1.8" data-mini-rdoc="QuantileGH::integer">integer</a> scalar, number of clusters</dd>
<dt>method</dt>
<dd><a href="/link/character?package=QuantileGH&version=0.1.8" data-mini-rdoc="QuantileGH::character">character</a> scalar,
only <code>'reassign_tkmeans'</code> (default) supported yet</dd>
<dt>alpha</dt>
<dd><a href="/link/numeric?package=QuantileGH&version=0.1.8" data-mini-rdoc="QuantileGH::numeric">numeric</a> scalar, proportion of observations to be trimmed in
trimmed \(k\)-means algorithm tkmeans</dd>
<dt>...</dt>
<dd>additional parameters, currently not in use</dd></dl>

Arguments

To create a <a href='https://rdrr.io/r/base/list.html'>list</a> of observations based on (modified) \(k\)-means algorithm.

Data Clusters by (modified) \(k\)-Means — klist

<dl>

<dt>x</dt>
<dd><a href='https://rdrr.io/r/base/numeric.html'>numeric</a> <a href='https://rdrr.io/r/base/vector.html'>vector</a>, one-dimensional observations</dd>


<dt>K</dt>
<dd><a href='https://rdrr.io/r/base/integer.html'>integer</a> scalar, number of clusters</dd>


<dt>method</dt>
<dd><a href='https://rdrr.io/r/base/character.html'>character</a> scalar,
only <code>'reassign_tkmeans'</code> (default) supported yet</dd>


<dt>alpha</dt>
<dd><a href='https://rdrr.io/r/base/numeric.html'>numeric</a> scalar, proportion of observations to be trimmed in
trimmed \(k\)-means algorithm tkmeans</dd>


<dt>...</dt>
<dd>additional parameters, currently not in use</dd>

</dl>

klist: Data Clusters by (modified) \(k\)-Means

Description

Usage

Value

Arguments

See Also