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 |