computeCVError

Computes the V-fold CV error for a linear regression model using fast LS fitting.

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

computeCVError function

<dl><dt>x</dt>
<dd>Design matrix (imputed).</dd>
<dt>y</dt>
<dd>Response vector (imputed).</dd>
<dt>active_set</dt>
<dd>Indices of predictors to include.</dd>
<dt>folds</dt>
<dd>Number of folds (default 5).</dd></dl>

Arguments

Compute Cross-Validated Prediction Error (Internal) — computeCVError

<dl>

<dt>x</dt>
<dd>Design matrix (imputed).</dd>


<dt>y</dt>
<dd>Response vector (imputed).</dd>


<dt>active_set</dt>
<dd>Indices of predictors to include.</dd>


<dt>folds</dt>
<dd>Number of folds (default 5).</dd>

</dl>

computeCVError: Compute Cross-Validated Prediction Error (Internal)

Description

Usage

Value

Arguments