triptych: Diagnostic Graphics to Evaluate Forecast Performance
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 + fileLICENSE |
| URL: | https://github.com/aijordan/triptych/,https://aijordan.github.io/triptych/ |
| NeedsCompilation: | yes |
| SystemRequirements: | C++20 |
| Materials: | README,NEWS |
| CRAN checks: | triptych results |
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