ncs_compute

Non-Conformity Score Computation Function

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 (2024) <DOI:10.48550/arXiv.2410.14507>.

David Randahl

pintervals

Model Agnostic Prediction Intervals

Jonathan P. Williams

Anders Hjort

ncs_compute function

<dl><dt>type</dt>
<dd>Type of non-conformity score to compute. Options include 'absolute_error', 'raw_error', 'relative_error', 'relative_error2', and 'heterogeneous_error'.</dd>
<dt>pred</dt>
<dd>a numeric vector of predicted values</dd>
<dt>truth</dt>
<dd>a numeric vector of true values</dd>
<dt>coefs</dt>
<dd>a numeric vector of coefficients for the heterogeneous error model. Must be of length 2, where the first element is the intercept and the second element is the slope.</dd></dl>

Arguments

Non-Conformity Score Computation Function — ncs_compute

<dl>

<dt>type</dt>
<dd>Type of non-conformity score to compute. Options include 'absolute_error', 'raw_error', 'relative_error', 'relative_error2', and 'heterogeneous_error'.</dd>


<dt>pred</dt>
<dd>a numeric vector of predicted values</dd>


<dt>truth</dt>
<dd>a numeric vector of true values</dd>


<dt>coefs</dt>
<dd>a numeric vector of coefficients for the heterogeneous error model. Must be of length 2, where the first element is the intercept and the second element is the slope.</dd>

</dl>

ncs_compute: Non-Conformity Score Computation Function

Description

Usage

Arguments