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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.
Version: | 0.3.0 |
Depends: | R (≥ 3.5.0) |
Imports: | stats (≥ 3.0.0), dplyr (≥ 1.0.0), ggplot2 (≥ 3.0.0), purrr (≥ 1.0.0), RANN (≥ 2.0.0), tidyr (≥ 1.0.0), tibble (≥ 3.0.0), glue (≥ 1.0.0), magrittr (≥ 2.0.0), Hmisc (≥ 5.0.0), Rdpack |
Suggests: | knitr, rmarkdown, testthat (≥ 3.0.0) |
Published: | 2024-07-06 |
DOI: | 10.32614/CRAN.package.recalibratiNN |
Author: | Carolina Musso [aut, cre, cph], Ricardo Torres [aut, cph], João Reis [aut, cph], Guilherme Rodrigues [aut, ths, cph] |
Maintainer: | Carolina Musso <cmusso86 at gmail.com> |
BugReports: | https://github.com/cmusso86/recalibratiNN/issues |
License: | MIT + file LICENSE |
URL: | https://bdm.unb.br/handle/10483/38504, https://github.com/cmusso86/recalibratiNN, https://cmusso86.github.io/recalibratiNN/ |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | recalibratiNN results |
Reference manual: | recalibratiNN.pdf |
Vignettes: |
ANN ajusted to bidimensional data |
Package source: | recalibratiNN_0.3.0.tar.gz |
Windows binaries: | r-devel: recalibratiNN_0.3.0.zip, r-release: recalibratiNN_0.3.0.zip, r-oldrel: recalibratiNN_0.3.0.zip |
macOS binaries: | r-release (arm64): recalibratiNN_0.3.0.tgz, r-oldrel (arm64): recalibratiNN_0.3.0.tgz, r-release (x86_64): recalibratiNN_0.3.0.tgz, r-oldrel (x86_64): recalibratiNN_0.3.0.tgz |
Old sources: | recalibratiNN archive |
Please use the canonical form https://CRAN.R-project.org/package=recalibratiNN to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.