predict.MclustBounded

Predict clustering for univariate and multivariate bounded data based on
Gaussian finite mixture models estimated by <code>MclustBounded()</code>.

Extend the functionality of the 'mclust' package for Gaussian
finite mixture modeling by including: density estimation for data with
bounded support (Scrucca, 2019 <doi:10.1002/bimj.201800174>); modal
clustering using MEM (Modal EM) algorithm for Gaussian mixtures
(Scrucca, 2021 <doi:10.1002/sam.11527>); entropy estimation via
Gaussian mixture modeling (Robin & Scrucca, 2023
<doi:10.1016/j.csda.2022.107582>); Gaussian mixtures modeling of
financial log-returns (Scrucca, 2024 <doi:10.3390/e26110907>).

Luca Scrucca

mclustAddons

Addons for the 'mclust' Package

predict.MclustBounded function

<dl><dt>object</dt>
<dd>An object of class <code>'MclustBounded'</code> resulting
from a call to <code>MclustBounded()</code>.</dd>
<dt>newdata</dt>
<dd>A numeric vector, matrix, or data frame of observations. If
missing the density is computed for the input data obtained from the call to
<code>MclustBounded()</code>.</dd>
<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd></dl>

Arguments

Author

Model-based clustering estimation for bounded data — predict.MclustBounded

<dl>

<dt>object</dt>
<dd>An object of class <code>'MclustBounded'</code> resulting
from a call to <code>MclustBounded()</code>.</dd>


<dt>newdata</dt>
<dd>A numeric vector, matrix, or data frame of observations. If
missing the density is computed for the input data obtained from the call to
<code>MclustBounded()</code>.</dd>


<dt>...</dt>
<dd>Further arguments passed to or from other methods.</dd>

</dl>

predict.MclustBounded: Model-based clustering estimation for bounded data

Description

Usage

Value

Arguments

Author

References

See Also