Function reference
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scoringutils
scoringutils-package
- scoringutils: Utilities for Scoring and Assessing Predictions
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avail_forecasts()
- Display Number of Forecasts Available
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check_forecasts()
- Check forecasts
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find_duplicates()
- Find duplicate forecasts
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log_shift()
- Log transformation with an additive shift
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print(<scoringutils_check>)
- Print output from
check_forecasts()
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transform_forecasts()
- Transform forecasts and observed values
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score()
- Evaluate forecasts
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add_coverage()
- Add coverage of central prediction intervals
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correlation()
- Correlation Between Metrics
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pairwise_comparison()
- Do Pairwise Comparisons of Scores
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pit()
- Probability Integral Transformation (data.frame Format)
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summarise_scores()
summarize_scores()
- Summarise scores as produced by
score()
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abs_error()
- Absolute Error
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ae_median_quantile()
- Absolute Error of the Median (Quantile-based Version)
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ae_median_sample()
- Absolute Error of the Median (Sample-based Version)
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bias_quantile()
- Determines Bias of Quantile Forecasts
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bias_range()
- Determines Bias of Quantile Forecasts based on the range of the prediction intervals
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bias_sample()
- Determines bias of forecasts
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brier_score()
- Brier Score
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crps_sample()
- Ranked Probability Score
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dss_sample()
- Dawid-Sebastiani Score
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interval_score()
- Interval Score
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logs_binary()
- Log Score for Binary outcomes
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logs_sample()
- Logarithmic score
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mad_sample()
- Determine dispersion of a probabilistic forecast
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pit_sample()
- Probability Integral Transformation (sample-based version)
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quantile_score()
- Quantile Score
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se_mean_sample()
- Squared Error of the Mean (Sample-based Version)
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squared_error()
- Squared Error
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merge_pred_and_obs()
- Merge Forecast Data And Observations
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sample_to_quantile()
- Change Data from a Sample Based Format to a Quantile Format
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set_forecast_unit()
- Set unit of a single forecast manually
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plot_avail_forecasts()
- Visualise Where Forecasts Are Available
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plot_correlation()
- Plot Correlation Between Metrics
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plot_heatmap()
- Create a Heatmap of a Scoring Metric
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plot_interval_coverage()
- Plot Interval Coverage
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plot_pairwise_comparison()
- Plot Heatmap of Pairwise Comparisons
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plot_pit()
- PIT Histogram
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plot_predictions()
- Plot Predictions vs True Values
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plot_quantile_coverage()
- Plot Quantile Coverage
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plot_ranges()
- Plot Metrics by Range of the Prediction Interval
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plot_score_table()
- Plot Coloured Score Table
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plot_wis()
- Plot Contributions to the Weighted Interval Score
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theme_scoringutils()
- Scoringutils ggplot2 theme
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check_equal_length()
- Check Length
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check_metrics()
- Check whether the desired metrics are available in scoringutils
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check_not_null()
- Check Variable is not NULL
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check_predictions()
- Check Prediction Input For Lower-level Scoring Functions
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check_quantiles()
- Check that quantiles are valid
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check_summary_params()
- Check input parameters for
summarise_scores()
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check_true_values()
- Check Observed Value Input For Lower-level Scoring Functions
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collapse_messages()
- Collapse several messages to one
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compare_two_models()
- Compare Two Models Based on Subset of Common Forecasts
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delete_columns()
- Delete Columns From a Data.table
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geom_mean_helper()
- Calculate Geometric Mean
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get_forecast_unit()
- Get unit of a single forecast
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get_prediction_type()
- Get prediction type of a forecast
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get_protected_columns()
- Get protected columns from a data frame
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get_target_type()
- Get type of the target true values of a forecast
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infer_rel_skill_metric()
- Infer metric for pairwise comparisons
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is_scoringutils_check()
- Check whether object has been checked with check_forecasts()
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pairwise_comparison_one_group()
- Do Pairwise Comparison for one Set of Forecasts
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permutation_test()
- Simple permutation test
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prediction_is_quantile()
- Check if predictions are quantile forecasts
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quantile_to_range_long()
- Change Data from a Plain Quantile Format to a Long Range Format
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range_long_to_quantile()
- Change Data from a Range Format to a Quantile Format
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sample_to_range_long()
- Change Data from a Sample Based Format to a Long Interval Range Format
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score_binary()
- Evaluate forecasts in a Binary Format
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score_quantile()
- Evaluate forecasts in a Quantile-Based Format
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score_sample()
- Evaluate forecasts in a Sample-Based Format (Integer or Continuous)
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scoringutils
scoringutils-package
- scoringutils: Utilities for Scoring and Assessing Predictions
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example_binary
- Binary Forecast Example Data
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example_continuous
- Continuous Forecast Example Data
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example_integer
- Integer Forecast Example Data
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example_point
- Point Forecast Example Data
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example_quantile
- Quantile Example Data
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example_quantile_forecasts_only
- Quantile Example Data - Forecasts only
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example_truth_only
- Truth data only
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available_metrics()
- Available metrics in scoringutils
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metrics
- Summary information for selected metrics