add_relative_skill      Add relative skill scores based on pairwise
                        comparisons
ae_median_quantile      Absolute error of the median (quantile-based
                        version)
ae_median_sample        Absolute error of the median (sample-based
                        version)
as_forecast_binary      Create a 'forecast' object for binary forecasts
as_forecast_doc_template
                        General information on creating a 'forecast'
                        object
as_forecast_generic     Common functionality for as_forecast_<type>
                        functions
as_forecast_multivariate_point
                        Create a 'forecast' object for multivariate
                        point forecasts
as_forecast_multivariate_sample
                        Create a 'forecast' object for sample-based
                        multivariate forecasts
as_forecast_nominal     Create a 'forecast' object for nominal
                        forecasts
as_forecast_ordinal     Create a 'forecast' object for ordinal
                        forecasts
as_forecast_point       Create a 'forecast' object for point forecasts
as_forecast_quantile    Create a 'forecast' object for quantile-based
                        forecasts
as_forecast_sample      Create a 'forecast' object for sample-based
                        forecasts
assert_dims_ok_scalar   Assert Inputs Have Matching Dimensions
assert_forecast.forecast_binary
                        Assert that input is a forecast object and
                        passes validations
assert_forecast_generic
                        Validation common to all forecast types
assert_forecast_type    Assert that forecast type is as expected
assert_input_binary     Assert that inputs are correct for binary
                        forecast
assert_input_categorical
                        Assert that inputs are correct for categorical
                        forecasts
assert_input_interval   Assert that inputs are correct for
                        interval-based forecast
assert_input_multivariate_sample
                        Assert that inputs are correct for sample-based
                        forecast
assert_input_nominal    Assert that inputs are correct for nominal
                        forecasts
assert_input_ordinal    Assert that inputs are correct for ordinal
                        forecasts
assert_input_point      Assert that inputs are correct for point
                        forecast
assert_input_quantile   Assert that inputs are correct for
                        quantile-based forecast
assert_input_sample     Assert that inputs are correct for sample-based
                        forecast
bias_quantile           Determines bias of quantile forecasts
bias_sample             Determine bias of forecasts
check_columns_present   Check column names are present in a data.frame
check_dims_ok_scalar    Check Inputs Have Matching Dimensions
check_duplicates        Check that there are no duplicate forecasts
check_input_binary      Check that inputs are correct for binary
                        forecast
check_input_interval    Check that inputs are correct for
                        interval-based forecast
check_input_point       Check that inputs are correct for point
                        forecast
check_input_quantile    Check that inputs are correct for
                        quantile-based forecast
check_input_sample      Check that inputs are correct for sample-based
                        forecast
check_number_per_forecast
                        Check that all forecasts have the same number
                        of rows
check_numeric_vector    Check whether an input is an atomic vector of
                        mode 'numeric'
check_try               Helper function to convert assert statements
                        into checks
crps_sample             (Continuous) ranked probability score
dss_sample              Dawid-Sebastiani score
energy_score_multivariate
                        Energy score for multivariate forecasts
example_binary          Binary forecast example data
example_multivariate_sample
                        Multivariate forecast example data
example_nominal         Nominal example data
example_ordinal         Ordinal example data
example_point           Point forecast example data
example_quantile        Quantile example data
example_sample_continuous
                        Continuous forecast example data
example_sample_discrete
                        Discrete forecast example data
get_correlations        Calculate correlation between metrics
get_coverage            Get quantile and interval coverage values for
                        quantile-based forecasts
get_duplicate_forecasts
                        Find duplicate forecasts
get_forecast_counts     Count number of available forecasts
get_forecast_type       Get forecast type from forecast object
get_forecast_unit       Get unit of a single forecast
get_grouping            Get grouping for a multivariate forecast
get_metrics             Get metrics
get_metrics.forecast_binary
                        Get default metrics for binary forecasts
get_metrics.forecast_multivariate_point
                        Get default metrics for multivariate point
                        forecasts
get_metrics.forecast_multivariate_sample
                        Get default metrics for sample-based forecasts
get_metrics.forecast_nominal
                        Get default metrics for nominal forecasts
get_metrics.forecast_ordinal
                        Get default metrics for nominal forecasts
get_metrics.forecast_point
                        Get default metrics for point forecasts
get_metrics.forecast_quantile
                        Get default metrics for quantile-based
                        forecasts
get_metrics.forecast_sample
                        Get default metrics for sample-based forecasts
get_metrics.scores      Get names of the metrics that were used for
                        scoring
get_pairwise_comparisons
                        Obtain pairwise comparisons between models
get_pit_histogram.forecast_quantile
                        Probability integral transformation histogram
get_type                Get type of a vector or matrix of observed
                        values or predictions
interval_coverage       Interval coverage (for quantile-based
                        forecasts)
interval_score          Interval score
is_forecast_binary      Test whether an object is a forecast object
log_shift               Log transformation with an additive shift
logs_categorical        Log score for categorical outcomes
logs_sample             Logarithmic score (sample-based version)
mad_sample              Determine dispersion of a probabilistic
                        forecast
pit_histogram_sample    Probability integral transformation for counts
plot_correlations       Plot correlation between metrics
plot_forecast_counts    Visualise the number of available forecasts
plot_heatmap            Create a heatmap of a scoring metric
plot_interval_coverage
                        Plot interval coverage
plot_pairwise_comparisons
                        Plot heatmap of pairwise comparisons
plot_quantile_coverage
                        Plot quantile coverage
plot_wis                Plot contributions to the weighted interval
                        score
print.forecast          Print information about a forecast object
quantile_score          Quantile score
rps_ordinal             Ranked Probability Score for ordinal outcomes
score.forecast_binary   Evaluate forecasts
scoring-functions-binary
                        Metrics for binary outcomes
se_mean_sample          Squared error of the mean (sample-based
                        version)
select_metrics          Select metrics from a list of functions
set_forecast_unit       Set unit of a single forecast manually
summarise_scores        Summarise scores as produced by 'score()'
test_columns_present    Test whether all column names are present in a
                        data.frame
theme_scoringutils      Scoringutils ggplot2 theme
transform_forecasts     Transform forecasts and observed values
validate_metrics        Validate metrics
variogram_score_multivariate
                        Variogram score for multivariate forecasts
variogram_score_multivariate_point
                        Variogram score for multivariate point
                        forecasts
wis                     Weighted interval score (WIS)
