clus2norMix

a grouping/clustering vector with values in
 \(\{1,..,K\}\); possibly a <code><a rd-options="" href="/link/factor?package=nor1mix&version=1.3-0" data-mini-rdoc="nor1mix::factor">factor</a></code>.

numeric vector of (original) data (of the same length as <code>gr</code>).

name for <code><a rd-options="" href="/link/norMix?package=nor1mix&version=1.3-0" data-mini-rdoc="nor1mix::norMix">norMix</a>()</code> object; constructed from
 the call by default.

name

Simple transformation of a clustering or grouping to a normal mixture
 object (class <code>"norMix"</code>, see, <code>norMix</code>.

models

cluster

Onedimensional Normal (i.e. Gaussian) Mixture Models Classes,
for, e.g., density estimation or clustering algorithms research and teaching;
providing the widely used Marron-Wand densities.  Efficient random
number generation and graphics. Fitting to data by efficient ML (Maximum
Likelihood) or traditional EM estimation.

Martin Maechler

nor1mix

Normal aka Gaussian (1-d) Mixture Models (S3 Classes and
Methods)

Friedrich Leisch

Erik Jørgensen

clus2norMix function

<dl> <dt>gr</dt>
<dd>a grouping/clustering vector with values in
 \(\{1,..,K\}\); possibly a <code><a href="/link/factor?package=nor1mix&version=1.3-0" data-mini-rdoc="nor1mix::factor">factor</a></code>.</dd> <dt>x</dt>
<dd>numeric vector of (original) data (of the same length as <code>gr</code>).</dd> <dt>name</dt>
<dd>name for <code>norMix()</code> object; constructed from
 the call by default.</dd></dl>

Arguments

Author

Transform Clustering / Grouping to Normal Mixture — clus2norMix

<dl>

 <dt>gr</dt>
<dd>a grouping/clustering vector with values in
 \(\{1,..,K\}\); possibly a <code><a href='https://rdrr.io/r/base/factor.html'>factor</a></code>.</dd>

 <dt>x</dt>
<dd>numeric vector of (original) data (of the same length as <code>gr</code>).</dd>

 <dt>name</dt>
<dd>name for <code>norMix()</code> object; constructed from
 the call by default.</dd>

</dl>

clus2norMix: Transform Clustering / Grouping to Normal Mixture

Description

Usage

Value

Arguments

Author

See Also

Examples