Package: triptych 0.1.3
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>.
Authors:
triptych_0.1.3.tar.gz
triptych_0.1.3.zip(r-4.5)triptych_0.1.3.zip(r-4.4)triptych_0.1.3.zip(r-4.3)
triptych_0.1.3.tgz(r-4.4-x86_64)triptych_0.1.3.tgz(r-4.4-arm64)triptych_0.1.3.tgz(r-4.3-x86_64)triptych_0.1.3.tgz(r-4.3-arm64)
triptych_0.1.3.tar.gz(r-4.5-noble)triptych_0.1.3.tar.gz(r-4.4-noble)
triptych_0.1.3.tgz(r-4.4-emscripten)triptych_0.1.3.tgz(r-4.3-emscripten)
triptych.pdf |triptych.html✨
triptych/json (API)
NEWS
# Install 'triptych' in R: |
install.packages('triptych', repos = c('https://aijordan.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/aijordan/triptych/issues
- ex_binary - Example data set of binary observations and probability forecasts
Last updated 5 months agofrom:62f8591e13. Checks:OK: 9. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 10 2024 |
R-4.5-win-x86_64 | OK | Nov 10 2024 |
R-4.5-linux-x86_64 | OK | Nov 10 2024 |
R-4.4-win-x86_64 | OK | Nov 10 2024 |
R-4.4-mac-x86_64 | OK | Nov 10 2024 |
R-4.4-mac-aarch64 | OK | Nov 10 2024 |
R-4.3-win-x86_64 | OK | Nov 10 2024 |
R-4.3-mac-x86_64 | OK | Nov 10 2024 |
R-4.3-mac-aarch64 | OK | Nov 10 2024 |
Exports:add_confidenceadd_consistencyas_mcbdscas_murphyas_reliabilityas_rocautoplotestimatesforecastsmcbdscmurphyobservationsregionsreliabilityresampling_Bernoulliresampling_casesroctriptych
Dependencies:classclicolorspacecpp11dplyrfansifarvergenericsgeomtextpathggplot2ggrepelgluegtableisobandlabelinglatticelifecyclemagrittrMASSMatrixmgcvmonotonemunsellnlmepatchworkpillarpkgconfigplyrpROCpurrrR6RColorBrewerRcpprlangscalesstringistringrsystemfontstextshapingtibbletidyrtidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Accessing original forecast and observation data for triptych objects | accessors forecasts observations |
Adding confidence regions | add_confidence |
Adding consistency regions for reliability curves | add_consistency |
Accessing diagnostic estimate data | estimates estimates.triptych_mcbdsc estimates.triptych_murphy estimates.triptych_reliability estimates.triptych_roc |
Example data set of binary observations and probability forecasts | ex_binary |
Evaluation of forecasts using score decompositions | as_mcbdsc mcbdsc |
Evaluation of forecasts using Murphy curves | as_murphy murphy |
Plot methods for the triptych classes | autoplot.triptych autoplot.triptych_mcbdsc autoplot.triptych_murphy autoplot.triptych_reliability autoplot.triptych_roc plot.triptych plot.triptych_mcbdsc plot.triptych_murphy plot.triptych_reliability plot.triptych_roc |
Accessing confidence/consistency region data | regions regions.triptych_mcbdsc regions.triptych_murphy regions.triptych_reliability regions.triptych_roc |
Evaluation of forecasts using reliability curves | as_reliability reliability |
Bootstrap (binary) observation resampling for triptych objects | resampling_Bernoulli resampling_Bernoulli.triptych_murphy resampling_Bernoulli.triptych_reliability resampling_Bernoulli.triptych_roc |
Bootstrap case resampling for triptych objects | resampling_cases resampling_cases.triptych_murphy resampling_cases.triptych_reliability resampling_cases.triptych_roc |
Evaluation of forecasts using ROC curves | as_roc roc |
Evaluation of forecasts using a Triptych | triptych |