Overall predictive performance is measured by a mean score (or loss), which decomposes into miscalibration, discrimination, and uncertainty components. The main focus is visualization of these distinct and complementary aspects in joint displays. See Dimitriadis, Gneiting, Jordan, Vogel (2024) <doi:10.1016/j.ijforecast.2023.09.007>.
Version: 0.1.3 Depends: R (≥ 4.2) Imports: ggplot2, patchwork, pROC, monotone, tidyr, vctrs, dplyr, purrr, tibble, rlang, tidyselect, class, scales, geomtextpath (≥ 0.1.4), ggrepel LinkingTo: cpp11 Suggests: testthat (≥ 3.0.0) Published: 2024-06-13 DOI: 10.32614/CRAN.package.triptych Author: Timo Dimitriadis [aut, cph], Alexander I. Jordan [aut, cre, cph] Maintainer: Alexander I. Jordan <alexander.jordan at h-its.org> License: MIT + file LICENSE URL: https://github.com/aijordan/triptych/, https://aijordan.github.io/triptych/ NeedsCompilation: yes SystemRequirements: C++20 Materials: README NEWS CRAN checks: triptych results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=triptych to link to this page.
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