The parameters Maximum Likelihood Estimation is obtained by numerical optimization.

An implementation for computing Optimal B-Robust Estimators of two-parameter
distribution. The procedure is composed of some equations
that are evaluated alternatively until the solution is reached. Some tools
for analyzing the estimates are included. The most relevant is
covariance matrix computation using a closed formula.

Fabio Piacenza

OBRE

Optimal B-Robust Estimator Tools

Andrea Riboldi

Ivan Luciano Danesi

Oliver Kuehnle

Davide Di Vincenzo

Ruben Ciaponi

Stephen Allen

Novella Saccenti

Annarita Filippi

MLE function

<dl><dt>nvData</dt>
<dd>The vector of the data.</dd>
<dt>strDistribution</dt>
<dd>The distribution name.</dd>
<dt>lDensityExpr</dt>
<dd>The distribution expression,</dd></dl>

Arguments

Numerical Maximum Likelihood Estimator — MLE

<dl>

<dt>nvData</dt>
<dd>The vector of the data.</dd>


<dt>strDistribution</dt>
<dd>The distribution name.</dd>


<dt>lDensityExpr</dt>
<dd>The distribution expression,</dd>

</dl>

MLE: Numerical Maximum Likelihood Estimator

Description

Usage

Value

Arguments