wcss_compute

Function to Compute the Within-Cluster Sum of Squares (WCSS) for a Set of Clusters

internal

Provides tools for estimating model-agnostic prediction intervals using conformal prediction, bootstrapping, and parametric prediction intervals. The package is designed for ease of use, offering intuitive functions for both binned and full conformal prediction methods, as well as parametric interval estimation with diagnostic checks. Currently only working for continuous predictions. For details on the conformal and bin-conditional conformal prediction methods, see Randahl, Williams, and Hegre (2026) <DOI:10.1017/pan.2025.10010>.

David Randahl

pintervals

Model Agnostic Prediction Intervals

Jonathan P. Williams

Anders Hjort

wcss_compute function

<dl><dt>ncs</dt>
<dd>Vector of non-conformity scores</dd>
<dt>class_vec</dt>
<dd>Vector of class labels</dd>
<dt>cluster</dt>
<dd>Vector of cluster labels</dd>
<dt>q</dt>
<dd>Quantiles to use for the qECDFs, default is a sequence from 0.1 to 0.9 in steps of 0.1</dd></dl>

Arguments

Function to Compute the Within-Cluster Sum of Squares (WCSS) for a Set of Clusters — wcss_compute

<dl>

<dt>ncs</dt>
<dd>Vector of non-conformity scores</dd>


<dt>class_vec</dt>
<dd>Vector of class labels</dd>


<dt>cluster</dt>
<dd>Vector of cluster labels</dd>


<dt>q</dt>
<dd>Quantiles to use for the qECDFs, default is a sequence from 0.1 to 0.9 in steps of 0.1</dd>

</dl>

wcss_compute: Function to Compute the Within-Cluster Sum of Squares (WCSS) for a Set of Clusters

Description

Usage

Value

Arguments