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 + 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:
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