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scoringRules (version 1.1.3)

Scoring Rules for Parametric and Simulated Distribution Forecasts

Description

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 , .

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Install

install.packages('scoringRules')

Monthly Downloads

4,690

Version

1.1.3

License

GPL (>= 2)

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Maintainer

Fabian Krueger

Last Published

September 18th, 2024

Functions in scoringRules (1.1.3)

scores_binom

Calculating scores for the binomial distribution
run_mcstudy

Run the Monte Carlo study by KLTG (2021), or a smaller version thereof
scores

Generic Scoring Rule Calculation
print.mcstudy

Simple print function for object of class mcstudy
scores_gpd

Calculating scores for the generalized Pareto distribution
scores_gev

Calculating scores for the generalized extreme value distribution
print.casestudy

Simple print method for object of class casestudy
scores_lnorm

Calculating scores for the log-normal distribution
scores_llogis

Calculating scores for the log-logistic distribution
scores_llapl

Calculating scores for the log-Laplace distribution
scores_logis

Calculating scores for the logistic distribution
scores_hyper

Calculating scores for the hypergeometric distribution
scores_lapl

Calculating scores for the Laplace distribution
scores_gamma

Calculating scores for the gamma distribution
scores_2pnorm

Calculating scores for the two-piece-normal distribution
scores_2pexp

Calculating scores for the two-piece-exponential distribution
scores_norm

Calculating scores for the normal distribution
scores_exp

Calculating scores for the exponential distribution
scores_nbinom

Calculating scores for the negative binomial distribution
scores_mixnorm

Calculating scores for a mixture of normal distributions.
scores_pois

Calculating scores for the Poisson distribution
scores_sample_univ

Scoring Rules for Simulated Forecast Distributions
summary.casestudy

Summary method for class casestudy
scores_sample_multiv

Multivariate Scoring Rules for Simulated Forecast Distributions
scores_moments

Scoring Rules for a Vector of Moments
scores_sample_univ_weighted

Weighted Scoring Rules for Simulated Forecast Distributions
summary.mcstudy

Simple summary method for class mcstudy
scores_quantiles

Quantile and interval scores
scores_sample_multiv_weighted

Weighted Multivariate Scoring Rules for Simulated Forecast Distributions
scores_unif

Calculating scores for the uniform distribution
scores_t

Calculating scores for Student's \(t\)-distribution
rps_probs

Ranked Probability Score
run_casestudy

Run the case study in KLTG (2021), or a smaller version thereof
get_weight_func

Default Weight and Chaining Functions
scores_beta

Calculating scores for the beta distribution
logs.numeric

Logarithmic Score for Parametric Forecast Distributions
plot.casestudy

Plot the output of run_casestudy
crps.numeric

Continuous Ranked Probability Score for Parametric Forecast Distributions
plot.mcstudy

Plot the output of run_mcstudy
GDP data

Data and forecasts for US GDP growth
Supplementary distributions: Positive real line

Supplementary distributions (not in base R) supported on the positive real line.
Supplementary distributions: Real line

Supplementary distributions (not in base R) supported on the real line.
Supplementary distributions: Variable support

Supplementary distributions (not in base R) with variable support.
ar_ms

Bayesian analysis of a Markov Switching autoregressive model