scoringfunctions-package: Overview of the functions in the scoringfunctions package

In scoringfunctions: A Collection of Loss Functions for Assessing Point Forecasts

Overview of the functions in the scoringfunctions package

Description

The scoringfunctions package implements consistent scoring (loss) functions and identification functions

Details

The package functions are categorized into the following classes:

• 1. Scoring functions

• 1.1. Consistent scoring functions for one-dimensional functionals

• 1.2. Consistent scoring functions for two-dimensional functionals

• 1.3. Consistent scoring functions for multi-dimensional functionals

• 2. Realised (average) score functions

• 2.1 Realised (average) score functions for one-dimensional functionals

• 3. Skill score functions

• 3.1 Skill score functions for one-dimensional functionals

• 4. Identification functions

• 4.1. Identification functions for one-dimensional functionals

• 4.2. Identification functions for two-dimensional functionals

• 5. Functions for sample levels

• 6. Supporting functions

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1. Scoring functions

1.1. Consistent scoring functions for one-dimensional functionals

\textit{1.1.1. Consistent scoring functions for the mean}

bregman1_sf: Bregman scoring function (type 1)

bregman2_sf: Bregman scoring function (type 2, Patton scoring function)

bregman3_sf: Bregman scoring function (type 3, QLIKE scoring function)

bregman4_sf: Bregman scoring function (type 4, Patton scoring function)

serr_sf: Squared error scoring function

\textit{1.1.2. Consistent scoring functions for expectiles}

expectile_sf: Asymmetric piecewise quadratic scoring function (expectile scoring function, expectile loss function)

\textit{1.1.3. Consistent scoring functions for the median}

aerr_sf: Absolute error scoring function

maelog_sf: MAE-LOG scoring function

maesd_sf: MAE-SD scoring function

\textit{1.1.4. Consistent scoring functions for quantiles}

gpl1_sf: Generalized piecewise linear power scoring function (type 1)

gpl2_sf: Generalized piecewise linear power scoring function (type 2)

quantile_sf: Asymmetric piecewise linear scoring function (quantile scoring function, quantile loss function)

\textit{1.1.5. Consistent scoring functions for Huber functionals}

ghuber_sf: Generalized Huber scoring function

huber_sf: Huber scoring function

\textit{1.1.6. Consistent scoring functions for other functionals}

aperr_sf: Absolute percentage error scoring function

bmedian_sf: \beta-median scoring function

linex_sf: LINEX scoring function

lqmean_sf: L_q-mean scoring function

lqquantile_sf: L_q-quantile scoring function

nmoment_sf: n-th moment scoring function

obsweighted_sf: Observation-weighted scoring function

relerr_sf: Relative error scoring function (MAE-PROP scoring function)

serrexp_sf: Squared error exp scoring function

serrlog_sf: Squared error log scoring function

serrpower_sf: Squared error of power transformations scoring function

serrsq_sf: Squared error of squares scoring function

sperr_sf: Squared percentage error scoring function

srelerr_sf: Squared relative error scoring function

1.2. Consistent scoring functions for two-dimensional functionals

interval_sf: Interval scoring function (Winkler scoring function)

mv_sf: Mean - variance scoring function

1.3. Consistent scoring functions for multi-dimensional functionals

errorspread_sf: Error - spread scoring function

2. Realised (average) score functions

2.1. Realised (average) score functions for one-dimensional functionals

\textit{2.1.1. Realised (average) score functions for the mean}

mse: Mean squared error (MSE)

\textit{2.1.2. Realised (average) score functions for expectiles}

expectile_rs: Realised expectile score

\textit{2.1.3. Realised (average) score functions for the median}

mae: Mean absolute error (MAE)

\textit{2.1.4. Realised (average) score functions for quantiles}

quantile_rs: Realised quantile score

\textit{2.1.5. Realised (average) score functions for Huber functionals}

huber_rs: Mean Huber score

\textit{2.1.6. Realised (average) score functions for other functionals}

mape: Mean absolute percentage error (MAPE)

mre: Mean relative error (MRE)

mspe: Mean squared percentage error (MSPE)

msre: Mean squared relative error (MSRE)

3. Skill score functions

3.1. Skill score functions for one-dimensional functionals

\textit{3.1.1. Skill score functions for the mean}

nse: Nash-Sutcliffe efficiency (NSE)

4. Identification functions

4.1. Identification functions for one-dimensional functionals

expectile_if: Expectile identification function

hubermean_if: Huber mean identification function

huberquantile_if: Huber quantile identification function

mean_if: Mean identification function

meanlog_if: Log-transformed identification function

nmoment_if: n-th moment identification function

quantile_if: Quantile identification function

4.2. Identification functions for two-dimensional functionals

mv_if: Mean - variance identification function

5. Functions for sample levels

quantile_level: Sample quantile level function

6. Supporting functions

capping_function: Capping function

scoringfunctions documentation built on April 4, 2025, 12:28 a.m.