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: 0.3.2 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: 2025-01-19 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 Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=recalibratiNN to link to this page.
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