calibrationband
Calibration Bands
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) doi:10.48550/arXiv.2203.04065.
- Version0.2.1
- R versionunknown
- LicenseGPL-3
- Needs compilation?Yes
- calibrationband citation info
- Last release08/09/2022
Documentation
Team
Marius Puke
Alexander Henzi
Show author detailsRolesAuthorTimo Dimitriadis
Show author detailsRolesAuthor
Insights
Last 30 days
This package has been downloaded 245 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 6 times.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Last 365 days
This package has been downloaded 3,104 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Jul 21, 2024 with 72 downloads.
The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.
Data provided by CRAN
Binaries
Dependencies
- Imports9 packages
- Linking To1 package