scoringutils2.0.0 package

Add relative skill scores based on pairwise comparisons

Absolute error of the median (quantile-based version)

Absolute error of the median (sample-based version)

Apply a list of functions to a data table of forecasts

Create a forecast object for binary forecasts

General information on creating a forecast object

Common functionality for as_forecast_<type> functions

Create a forecast object for nominal forecasts

Create a forecast object for point forecasts

Create a forecast object for quantile-based forecasts

Create a forecast object for sample-based forecasts

Create an object of class scores from data

Assert Inputs Have Matching Dimensions

Validation common to all forecast types

Assert that forecast type is as expected

Assert that input is a forecast object and passes validations

Assert that inputs are correct for binary forecast

Assert that inputs are correct for interval-based forecast

Assert that inputs are correct for nominal forecasts

Assert that inputs are correct for point forecast

Assert that inputs are correct for quantile-based forecast

Assert that inputs are correct for sample-based forecast

Validate an object of class scores

Compute bias for a single vector of quantile predictions

Determines bias of quantile forecasts

Determine bias of forecasts

Check column names are present in a data.frame

Check Inputs Have Matching Dimensions

Check that there are no duplicate forecasts

Check that inputs are correct for binary forecast

Check that inputs are correct for interval-based forecast

Check that inputs are correct for point forecast

Check that inputs are correct for quantile-based forecast

Check that inputs are correct for sample-based forecast

Check that all forecasts have the same number of rows

Check whether an input is an atomic vector of mode 'numeric'

Helper function to convert assert statements into checks

Clean forecast object

Compare a subset of common forecasts

(Continuous) ranked probability score

Documentation template for assert functions

Documentation template for check functions

Documentation template for test functions

Dawid-Sebastiani score

Ensure that an object is a data.table

Documentation template for forecast types

Calculate geometric mean

Calculate correlation between metrics

Get quantile and interval coverage values for quantile-based forecasts

Find duplicate forecasts

Count number of available forecasts

Get forecast type from forecast object

Get unit of a single forecast

Get default metrics for binary forecasts

Get default metrics for nominal forecasts

Get default metrics for point forecasts

Get default metrics for quantile-based forecasts

Get default metrics for sample-based forecasts

Get metrics

Get names of the metrics that were used for scoring

Obtain pairwise comparisons between models

Probability integral transformation histogram

Get protected columns from data

Get interval range belonging to a quantile

Get type of a vector or matrix of observed values or predictions

Illustration of required inputs for binary and point forecasts

Illustration of required inputs for nominal forecasts

Illustration of required inputs for quantile-based forecasts

Illustration of required inputs for sample-based forecasts

Helper function to interpolate the median prediction if it is not avai...

Interval coverage (for quantile-based forecasts)

Interval score

Test whether an object is a forecast object

Log transformation with an additive shift

Logarithmic score (sample-based version)

Determine dispersion of a probabilistic forecast

Class constructor for forecast objects

Construct an object of class scores

Do pairwise comparison for one set of forecasts

Simple permutation test

Probability integral transformation for counts

Plot correlation between metrics

Visualise the number of available forecasts

Create a heatmap of a scoring metric

Plot interval coverage

Plot heatmap of pairwise comparisons

Plot quantile coverage

Plot contributions to the weighted interval score

Print information about a forecast object

Quantile score

Transform from a quantile format to an interval format

Run a function safely

Change data from a sample-based format to a long interval range format

Evaluate forecasts

Metrics for binary outcomes

Log score for nominal outcomes

scoringutils: Utilities for Scoring and Assessing Predictions

Squared error of the mean (sample-based version)

Select metrics from a list of functions

Set unit of a single forecast manually

Summarise scores as produced by score()

Test whether column names are NOT present in a data.frame

Test whether all column names are present in a data.frame

Scoringutils ggplot2 theme

Transform forecasts and observed values

Validate metrics

Weighted interval score (WIS)