robustINIT

<p>the number of starting points to the algorithm, defaults to 10</p>

nstart

<p>Robust Initializer for RMBC algorithm, it depends on the package <code>ktaucenters</code></p>

A robust clustering algorithm (Model-Based) similar to Expectation
Maximization for finite mixture normal distributions is implemented,
its main advantage is that the estimator is resistant to outliers,
that means that results of parameter estimation are still correct when there
are atypical values in the sample
(see Gonzalez, Maronna, Yohai and Zamar (2021)
<arxiv:2102.06851>).

Juan Domingo Gonzalez

RMBC

robustINIT: robustINIT

Description

Usage

Arguments

Value