Package: recalibratiNN 0.3.1

recalibratiNN: Quantile Recalibration for Regression Models

Enables the diagnostics and enhancement of regression model calibration.It offers both global and local visualization tools for calibration diagnostics and provides one recalibration method: Torres R, Nott DJ, Sisson SA, Rodrigues T, Reis JG, Rodrigues GS (2024) <doi:10.48550/arXiv.2403.05756>. The method leverages on Probabilistic Integral Transform (PIT) values to both evaluate and perform the calibration of statistical models. For a more detailed description of the package, please refer to the bachelor's thesis available bellow.

Authors:Carolina Musso [aut, cre, cph], Ricardo Torres [aut, cph], João Reis [aut, cph], Guilherme Rodrigues [aut, ths, cph]

recalibratiNN_0.3.1.tar.gz
recalibratiNN_0.3.1.zip(r-4.5)recalibratiNN_0.3.1.zip(r-4.4)recalibratiNN_0.3.1.zip(r-4.3)
recalibratiNN_0.3.1.tgz(r-4.5-any)recalibratiNN_0.3.1.tgz(r-4.4-any)recalibratiNN_0.3.1.tgz(r-4.3-any)
recalibratiNN_0.3.1.tar.gz(r-4.5-noble)recalibratiNN_0.3.1.tar.gz(r-4.4-noble)
recalibratiNN_0.3.1.tgz(r-4.4-emscripten)recalibratiNN_0.3.1.tgz(r-4.3-emscripten)
recalibratiNN.pdf |recalibratiNN.html✨
recalibratiNN/json (API)
NEWS

# Install 'recalibratiNN' in R:
install.packages('recalibratiNN', repos = c('https://cmusso86.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/cmusso86/recalibratinn/issues

Pkgdown site:https://cmusso86.github.io

On CRAN:

Conda:

calibrationgaussian-modelsneural-networkprobabilityrecalibrationregression-models

5.32 score 7 stars 8 scripts 176 downloads 7 exports 74 dependencies

Last updated 2 months agofrom:7f04453f20. Checks:6 OK, 3 NOTE. Indexed: yes.

TargetResultLatest binary
Doc / VignettesOKMar 20 2025
R-4.5-winNOTEMar 20 2025
R-4.5-macNOTEMar 20 2025
R-4.5-linuxNOTEMar 20 2025
R-4.4-winOKMar 20 2025
R-4.4-macOKMar 20 2025
R-4.4-linuxOKMar 20 2025
R-4.3-winOKMar 20 2025
R-4.3-macOKMar 20 2025

Exports:gg_CD_globalgg_CD_localgg_PIT_globalgg_PIT_localPIT_globalPIT_localrecalibrate

Dependencies:backportsbase64encbslibcachemcheckmatecliclustercolorspacecpp11data.tabledigestdplyrevaluatefansifarverfastmapfontawesomeforeignFormulafsgenericsggplot2gluegridExtragtablehighrHmischtmlTablehtmltoolshtmlwidgetsisobandjquerylibjsonliteknitrlabelinglatticelifecyclemagrittrMASSMatrixmemoisemgcvmimemunsellnlmennetpillarpkgconfigpurrrR6RANNrappdirsrbibutilsRColorBrewerRdpackrlangrmarkdownrpartrstudioapisassscalesstringistringrtibbletidyrtidyselecttinytexutf8vctrsviridisviridisLitewithrxfunyaml

Recalibrating the predicitions of an ANN.

Rendered fromsimple_mlp.Rmdusingknitr::rmarkdownon Mar 20 2025.

Last update: 2025-01-19
Started: 2024-06-19