print.calibrationband

print.summary.calibrationband

Printing methods for <code>'calibrationband'</code> and
<code>'summary.calibrationband'</code> objects.

Package to assess the calibration of probabilistic classifiers using confidence bands for monotonic functions. Besides testing the classical goodness-of-fit null hypothesis of perfect calibration, the confidence bands calculated within that package facilitate inverted goodness-of-fit tests whose rejection allows for a sought-after conclusion of a sufficiently well-calibrated model. The package creates flexible graphical tools to perform these tests. For construction details see also Dimitriadis, Dümbgen, Henzi, Puke, Ziegel (2022) <arXiv:2203.04065>.

Marius Puke

calibrationband

Calibration Bands

Timo Dimitriadis

Alexander Henzi

print.calibrationband function

<dl><dt>x</dt>
<dd>object of class <code>calibrationband</code></dd>
<dt>...</dt>
<dd>Further arguments to be passed to or from methods;
in particular these passed to <code>autoplot.calibrationband</code></dd></dl>

Arguments

Print monotone confidence bands — print.calibrationband

<dl>

<dt>x</dt>
<dd>object of class <code>calibrationband</code></dd>


<dt>...</dt>
<dd>Further arguments to be passed to or from methods;
in particular these passed to <code>autoplot.calibrationband</code></dd>

</dl>

print.calibrationband: Print monotone confidence bands

Description

Usage

Value

Arguments

Details

See Also