cv_deviance_sb

K-fold deviance for an sb_gamlss configuration

Extends the 'SelectBoost' approach to Generalized Additive Models for
Location, Scale and Shape (GAMLSS). Implements bootstrap stability-selection
across parameter-specific formulas (mu, sigma, nu, tau) via gamlss::stepGAIC().
Includes optional standardization of predictors and helper functions for
corrected AIC calculation. More details can be found in Bertrand and Maumy (2024)
<https://hal.science/hal-05352041> that highlights correlation-aware resampling to improve
variable selection for GAMLSS and quantile regression when predictors are
numerous and highly correlated.

Frederic Bertrand

SelectBoost.gamlss

Stability-Selection via Correlated Resampling for 'GAMLSS'
Models

cv_deviance_sb function

<dl><dt>K</dt>
<dd>folds</dd>
<dt>build_fit</dt>
<dd>function(...) that returns an sb_gamlss object</dd>
<dt>data</dt>
<dd>data.frame used inside build_fit</dd></dl>

Arguments

K-fold deviance for an sb_gamlss configuration — cv_deviance_sb

<dl>

<dt>K</dt>
<dd>folds</dd>


<dt>build_fit</dt>
<dd>function(...) that returns an sb_gamlss object</dd>


<dt>data</dt>
<dd>data.frame used inside build_fit</dd>

</dl>

cv_deviance_sb: K-fold deviance for an sb_gamlss configuration

Description

Usage

Value

Arguments