selected.boostrq

Extract indices of selected base learners

Boosting Regression Quantiles is a component-wise boosting algorithm,
that embeds all boosting steps in the well-established framework
of quantile regression. It is initialized with the corresponding quantile,
uses a quantile-specific learning rate, and uses quantile regression as its base learner.
The package implements this algorithm and allows cross-validation and stability selection.

Stefan Linner

boostrq

Boosting Regression Quantiles

selected.boostrq function

<dl><dt>object</dt>
<dd>a boostrq object</dd>
<dt>...</dt>
<dd>additional arguments passed to callies</dd></dl>

Arguments

Extract indices of selected base learners — selected.boostrq

<dl>

<dt>object</dt>
<dd>a boostrq object</dd>


<dt>...</dt>
<dd>additional arguments passed to callies</dd>

</dl>

selected.boostrq: Extract indices of selected base learners

Description

Usage

Value

Arguments

Examples