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:Alexander I. Jordan [aut], Fabian Krueger [aut, cre], Sebastian Lerch [aut], Sam Allen [aut], Maximiliane Graeter [ctb]

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 = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/fk83/scoringrules/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3
Datasets:
  • gdp - Data and forecasts for US GDP growth
  • gdp_mcmc - Data and forecasts for US GDP growth

openblascpp

5.18 score 1 stars 12 packages 384 scripts 3.5k downloads 2 mentions 131 exports 8 dependencies

Last updated 3 months agofrom:a885f199a5. Checks:OK: 1 WARNING: 1. Indexed: no.

TargetResultDate
Doc / VignettesOKDec 13 2024
R-4.5-linux-x86_64WARNINGDec 13 2024

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 Dec 13 2024.

Last update: 2024-09-06
Started: 2017-11-03

R package scoringRules: Getting started

Alexander Jordan, Fabian Krüger, Sebastian Lerch

Rendered fromgettingstarted.Rmdusingknitr::rmarkdownon Dec 13 2024.

Last update: 2022-09-19
Started: 2016-07-06

Weighted scoringRules

Rendered fromarticle_weighted_scores.Rnwusingknitr::knitron Dec 13 2024.

Last update: 2024-09-06
Started: 2023-05-10

Readme and manuals

Help Manual

Help pageTopics
Bayesian analysis of a Markov Switching autoregressive modelar_ms
Continuous Ranked Probability Score for Parametric Forecast Distributionscrps.numeric
Data and forecasts for US GDP growthgdp gdp_mcmc
Default Weight and Chaining Functionsget_weight_func
Logarithmic Score for Parametric Forecast Distributionslogs.numeric
Plot the output of run_casestudyplot.casestudy
Plot the output of run_mcstudyplot.mcstudy
Simple print method for object of class casestudyprint.casestudy
Simple print function for object of class mcstudyprint.mcstudy
Ranked Probability Scorerps_probs
Run the case study in KLTG (2021), or a smaller version thereofrun_casestudy
Run the Monte Carlo study by KLTG (2021), or a smaller version thereofrun_mcstudy
Generic Scoring Rule Calculationcrps logs scores
Calculating scores for the two-piece-exponential distributioncrps_2pexp logs_2pexp scores_2pexp
Calculating scores for the two-piece-normal distributioncrps_2pnorm logs_2pnorm scores_2pnorm
Calculating scores for the beta distributioncrps_beta dss_beta logs_beta scores_beta
Calculating scores for the binomial distributioncrps_binom logs_binom scores_binom
Calculating scores for the exponential distributioncrps_exp crps_expM dss_exp logs_exp logs_exp2 scores_exp
Calculating scores for the gamma distributioncrps_gamma dss_gamma logs_gamma scores_gamma
Calculating scores for the generalized extreme value distributioncrps_gev dss_gev logs_gev scores_gev
Calculating scores for the generalized Pareto distributioncrps_gpd dss_gpd logs_gpd scores_gpd
Calculating scores for the hypergeometric distributioncrps_hyper logs_hyper scores_hyper
Calculating scores for the Laplace distributioncrps_lapl dss_lapl logs_lapl scores_lapl
Calculating scores for the log-Laplace distributioncrps_llapl dss_llapl logs_llapl scores_llapl
Calculating scores for the log-logistic distributioncrps_llogis dss_llogis logs_llogis scores_llogis
Calculating scores for the log-normal distributioncrps_lnorm dss_lnorm logs_lnorm scores_lnorm
Calculating scores for the logistic distributioncrps_clogis crps_gtclogis crps_logis crps_tlogis dss_logis gradcrps_clogis gradcrps_logis gradcrps_tlogis hesscrps_clogis hesscrps_logis hesscrps_tlogis logs_logis logs_tlogis scores_logis
Calculating scores for a mixture of normal distributions.crps_mixnorm crps_mixnorm_int dss_mixnorm logs_mixnorm scores_mixnorm
Scoring Rules for a Vector of Momentsdss_moments ess_moments scores_moments
Calculating scores for the negative binomial distributioncrps_nbinom dss_nbinom logs_nbinom scores_nbinom
Calculating scores for the normal distributioncrps_cnorm crps_gtcnorm crps_norm crps_tnorm dss_norm gradcrps_cnorm gradcrps_norm gradcrps_tnorm hesscrps_cnorm hesscrps_norm hesscrps_tnorm logs_norm logs_tnorm scores_norm
Calculating scores for the Poisson distributioncrps_pois dss_pois logs_pois scores_pois
Quantile and interval scoresints_quantiles ints_sample qs_quantiles qs_sample scores_quantiles
Multivariate Scoring Rules for Simulated Forecast Distributionses_sample mmds_sample scores_sample_multiv vs_sample
Weighted Multivariate Scoring Rules for Simulated Forecast Distributionsowes_sample owmmds_sample owvs_sample scores_sample_multiv_weighted twes_sample twmmds_sample twvs_sample
Scoring Rules for Simulated Forecast Distributionscrps_sample dss_sample logs_sample scores_sample_univ
Weighted Scoring Rules for Simulated Forecast Distributionsclogs_sample owcrps_sample scores_sample_univ_weighted twcrps_sample
Calculating scores for Student's t-distributioncrps_ct crps_gtct crps_t crps_tt dss_t gradcrps_ct gradcrps_t gradcrps_tt hesscrps_ct hesscrps_t hesscrps_tt logs_t logs_tt scores_t
Calculating scores for the uniform distributioncrps_unif dss_unif logs_unif scores_unif
Summary method for class casestudysummary.casestudy
Simple summary method for class mcstudysummary.mcstudy
Supplementary distributions (not in base R) supported on the positive real line.fllapl fllogis
Supplementary distributions (not in base R) supported on the real line.f2pexp f2pnorm flapl fmixnorm
Supplementary distributions (not in base R) with variable support.fexp fgev fgpd flogis fnorm ft