plot.spconform_diagnose

Generates a multi-panel visual audit of marginal coverage, nonconformity
score QQ-distribution, conditional spatial strata coverage, and boundary
proximity effects.

Provides distribution-free, model-agnostic prediction
intervals for spatially and spatio-temporally dependent data using
localized conformal calibration. Implements locally weighted split
conformal prediction for geostatistical (point-referenced) data based on
spatial-distance kernels, and a neighbourhood-weighted conformal
procedure for areal (lattice) data based on graph adjacency structures.
Relaxes the standard exchangeability assumption using spatial proximity,
following the localized conformal framework of Mao, Martin and Reich
(2024) <doi:10.1080/01621459.2022.2147531>. Includes comprehensive
spatial diagnostic tools to audit empirical coverage, conditional
spatial strata, and boundary proximity effects.

Ahmed Sattar Jabbar

spconform

Conformal Prediction for Spatially and Spatio-Temporally
Dependent Data

plot.spconform_diagnose function

<dl><dt>x</dt>
<dd>An object of class <code>"spconform_diagnose"</code>.</dd>
<dt>...</dt>
<dd>Additional arguments passed to plotting functions.</dd></dl>

Arguments

Plot Diagnostic Audit for an spconform_diagnose Object — plot.spconform_diagnose

<dl>

<dt>x</dt>
<dd>An object of class <code>"spconform_diagnose"</code>.</dd>


<dt>...</dt>
<dd>Additional arguments passed to plotting functions.</dd>

</dl>

plot.spconform_diagnose: Plot Diagnostic Audit for an spconform_diagnose Object

Description

Usage

Value

Arguments