weightedMscale

weights

a tuning constant, if consistency to standard normal distribution is desired use
<code><a rd-options="" href="/link/normal_consistency_constants?package=RMBC&version=0.1.0" data-mini-rdoc="RMBC::normal_consistency_constants">normal_consistency_constants</a></code>

the initial scale value, defaults to 0

initialsc

weightedMscale
the M scale of an univariate sample (see reference below)

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

Robust Model Based Clustering

Victor J. Yohai

Ruben H. Zamar

Ricardo Maronna

weightedMscale function

a tuning constant, if consistency to standard normal distribution is desired use
<code><a rd-options='' href='normal_consistency_constants'>normal_consistency_constants</a></code>

weightedMscale: weightedMscale the M scale of an univariate sample (see reference below)

Description

Usage

Arguments

Value

References