computeFinalFit

Implements Stage 3: Fitting robust MM-estimators to the selected variable sets.

internal

Functions to perform robust variable selection and regression using the Fast and Scalable
Cellwise-Robust Ensemble (FSCRE) algorithm. The approach establishes a robust foundation
using the Detect Deviating Cells (DDC) algorithm and robust correlation estimates. It then
employs a competitive ensemble architecture where a robust Least Angle Regression (LARS)
engine proposes candidate variables and cross-validation arbitrates their assignment. A final
robust MM-estimator is applied to the selected predictors.

Anthony Christidis

srlars

Fast and Scalable Cellwise-Robust Ensemble

Gabriela Cohen-Freue

computeFinalFit function

<dl><dt>x.imp</dt>
<dd>Imputed design matrix.</dd>
<dt>y.imp</dt>
<dd>Imputed response vector.</dd>
<dt>active.sets</dt>
<dd>List of integer vectors (indices of selected variables).</dd>
<dt>compute_coef</dt>
<dd>Logical.</dd></dl>

Arguments

FSCRE Final Robust Fitting (Internal) — computeFinalFit

<dl>

<dt>x.imp</dt>
<dd>Imputed design matrix.</dd>


<dt>y.imp</dt>
<dd>Imputed response vector.</dd>


<dt>active.sets</dt>
<dd>List of integer vectors (indices of selected variables).</dd>


<dt>compute_coef</dt>
<dd>Logical.</dd>

</dl>

computeFinalFit: FSCRE Final Robust Fitting (Internal)

Description

Usage

Value

Arguments