Package: scoringRules 1.1.3
Fabian Krueger
scoringRules: Scoring Rules for Parametric and Simulated Distribution Forecasts
Dictionary-like reference for computing scoring rules in a wide range of situations. Covers both parametric forecast distributions (such as mixtures of Gaussians) and distributions generated via simulation. Further details can be found in the package vignettes <doi:10.18637/jss.v090.i12>, <doi:10.18637/jss.v110.i08>.
Authors:
scoringRules_1.1.3.tar.gz
scoringRules_1.1.3.tar.gz(r-4.5-noble)scoringRules_1.1.3.tar.gz(r-4.4-noble)
scoringRules_1.1.3.tgz(r-4.4-emscripten)scoringRules_1.1.3.tgz(r-4.3-emscripten)
scoringRules.pdf |scoringRules.html✨
scoringRules/json (API)
| # Install 'scoringRules' in R: |
| install.packages('scoringRules', repos = 'https://cloud.r-project.org') |
Bug tracker:https://github.com/fk83/scoringrules/issues0 issues
Last updated 7 months agofrom:a885f199a5. Checks:1 OK, 2 WARNING. Indexed: no.
| Target | Result | Latest binary |
|---|---|---|
| Doc / Vignettes | OK | Mar 13 2025 |
| R-4.5-linux-x86_64 | WARNING | Mar 13 2025 |
| R-4.4-linux-x86_64 | WARNING | Mar 13 2025 |
Exports:ar_msclogs_samplecrpscrps_2pexpcrps_2pnormcrps_betacrps_binomcrps_clogiscrps_cnormcrps_ctcrps_expcrps_expMcrps_gammacrps_gevcrps_gpdcrps_gtclogiscrps_gtcnormcrps_gtctcrps_hypercrps_laplcrps_llaplcrps_llogiscrps_lnormcrps_logiscrps_mixnormcrps_mixnorm_intcrps_nbinomcrps_normcrps_poiscrps_samplecrps_tcrps_tlogiscrps_tnormcrps_ttcrps_unifcrps.numericdss_betadss_expdss_gammadss_gevdss_gpddss_lapldss_llapldss_llogisdss_lnormdss_logisdss_mixnormdss_momentsdss_nbinomdss_normdss_poisdss_sampledss_tdss_unifes_sampleess_momentsf2pexpf2pnormfexpfgevfgpdflaplfllaplfllogisflogisfmixnormfnormftget_weight_funcgradcrps_clogisgradcrps_cnormgradcrps_ctgradcrps_logisgradcrps_normgradcrps_tgradcrps_tlogisgradcrps_tnormgradcrps_tthesscrps_clogishesscrps_cnormhesscrps_cthesscrps_logishesscrps_normhesscrps_thesscrps_tlogishesscrps_tnormhesscrps_ttints_quantilesints_samplelogslogs_2pexplogs_2pnormlogs_betalogs_binomlogs_explogs_exp2logs_gammalogs_gevlogs_gpdlogs_hyperlogs_lapllogs_llapllogs_llogislogs_lnormlogs_logislogs_mixnormlogs_nbinomlogs_normlogs_poislogs_samplelogs_tlogs_tlogislogs_tnormlogs_ttlogs_uniflogs.numericmmds_sampleowcrps_sampleowes_sampleowmmds_sampleowvs_sampleqs_quantilesqs_samplerps_probsrun_casestudyrun_mcstudytwcrps_sampletwes_sampletwmmds_sampletwvs_samplevs_sample
Dependencies:evaluatehighrknitrMASSRcppRcppArmadilloxfunyaml
Evaluating Probabilistic Forecasts with scoringRules
Rendered fromarticle.Rnwusingknitr::knitron Mar 13 2025.Last update: 2024-09-06
Started: 2017-11-03
R package scoringRules: Getting started
Rendered fromgettingstarted.Rmdusingknitr::rmarkdownon Mar 13 2025.Last update: 2022-09-19
Started: 2016-07-06
Weighted scoringRules
Rendered fromarticle_weighted_scores.Rnwusingknitr::knitron Mar 13 2025.Last update: 2024-09-06
Started: 2023-05-10
Citation
To cite scoringRules in publications use:
Jordan A, Krüger F, Lerch S (2019). “Evaluating Probabilistic Forecasts with scoringRules.” Journal of Statistical Software, 90(12), 1–37. doi:10.18637/jss.v090.i12.
If you use weighted scores (see ?scores_sample_univ_weighted and ?scores_sample_multiv_weighted), please also cite:
Allen S (2024). “Weighted scoringRules: Emphasizing Particular Outcomes When Evaluating Probabilistic Forecasts.” Journal of Statistical Software, 110(8), 1–26. doi:10.18637/jss.v110.i08.
Corresponding BibTeX entries:
@Article{,
title = {Evaluating Probabilistic Forecasts with {scoringRules}},
author = {Alexander Jordan and Fabian Kr\"uger and Sebastian
Lerch},
journal = {Journal of Statistical Software},
year = {2019},
volume = {90},
number = {12},
pages = {1--37},
doi = {10.18637/jss.v090.i12},
}
@Article{,
title = {Weighted {scoringRules}: Emphasizing Particular Outcomes
When Evaluating Probabilistic Forecasts},
author = {Sam Allen},
journal = {Journal of Statistical Software},
year = {2024},
volume = {110},
number = {8},
pages = {1--26},
doi = {10.18637/jss.v110.i08},
}
