mloc

Compute the M-estimate of location using an auxiliary estimate of the scale.

Robust penalized (adaptive) elastic net S and M estimators for
linear regression. The methods are proposed in
Cohen Freue, G. V., Kepplinger, D., Salibián-Barrera, M., and Smucler, E.
(2019) <https://projecteuclid.org/euclid.aoas/1574910036>.
The package implements the extensions and algorithms described in
Kepplinger, D. (2020) <doi:10.14288/1.0392915>.

David Kepplinger

pense

Penalized Elastic Net S/MM-Estimator of Regression

Matías Salibián-Barrera

Gabriela Cohen Freue

mloc function

<dl><dt>x</dt>
<dd>numeric values. Missing values are verbosely ignored.</dd>
<dt>scale</dt>
<dd>scale of the <code>x</code> values. If omitted, uses the <a href="/link/mad()?package=pense&version=2.2.2" data-mini-rdoc="pense::mad()">mad()</a>.</dd>
<dt>rho</dt>
<dd>the \(\rho\) function to use. See <code>rho_function()</code> for available functions.</dd>
<dt>cc</dt>
<dd>value of the tuning constant for the chosen \(\rho\) function.
By default, chosen to achieve 95% efficiency under the Normal distribution.</dd>
<dt>opts</dt>
<dd>a list of options for the M-estimating algorithm, see
<code>mscale_algorithm_options()</code> for details.</dd></dl>

Arguments

Compute the M-estimate of Location — mloc

<dl>

<dt>x</dt>
<dd>numeric values. Missing values are verbosely ignored.</dd>


<dt>scale</dt>
<dd>scale of the <code>x</code> values. If omitted, uses the <a href='https://rdrr.io/r/stats/mad.html'>mad()</a>.</dd>


<dt>rho</dt>
<dd>the \(\rho\) function to use. See <code>rho_function()</code> for available functions.</dd>


<dt>cc</dt>
<dd>value of the tuning constant for the chosen \(\rho\) function.
By default, chosen to achieve 95% efficiency under the Normal distribution.</dd>


<dt>opts</dt>
<dd>a list of options for the M-estimating algorithm, see
<code>mscale_algorithm_options()</code> for details.</dd>

</dl>

mloc: Compute the M-estimate of Location

Description

Usage

Value

Arguments

See Also