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Changelog

Source: NEWS.md

scoringutils 1.2.2

CRAN release: 2023-11-29

Package updates

  • scoringutils now depends on R 3.6. The change was made since packages testthat and lifecycle, which are used in scoringutils now require R 3.6. We also updated the Github action CI check to work with R 3.6 now.
  • Added a new PR template with a checklist of things to be included in PRs to facilitate the development and review process

Bug fixes

scoringutils 1.2.1

Package updates

  • This minor update fixes a few issues related to gh actions and the vignettes displayed at epiforecasts.io/scoringutils. It
    • Gets rid of the preferably package in _pkgdown.yml. The theme had a toggle between light and dark theme that didn’t work properly
    • Updates the gh pages deploy action to v4 and also cleans up files when triggered
    • Introduces a gh action to automatically render the Readme from Readme.Rmd
    • Removes links to vignettes that have been renamed

scoringutils 1.2.0

This major release contains a range of new features and bug fixes that have been introduced in minor releases since 1.1.0. The most important changes are:

  • Documentation updated to reflect changes since version 1.1.0, including new transform and workflow functions.
  • New set_forecast_unit() function allows manual setting of forecast unit.
  • summarise_scores() gains new across argument for summarizing across variables.
  • New transform_forecasts() and log_shift() functions allow forecast transformations. See the documentation for transform_forecasts() for more details and an example use case.
  • Input checks and test coverage improved for bias functions.
  • Bug fix in get_prediction_type() for integer matrix input.
  • Links to scoringutils paper and citation updates.
  • Warning added in interval_score() for small interval ranges.
  • Linting updates and improvements.

Thanks to @nikosbosse, @seabbs, and @sbfnk for code and review contributions. Thanks to @bisaloo for the suggestion to use a linting GitHub Action that only triggers on changes, and @adrian-lison for the suggestion to add a warning to interval_score() if the interval range is between 0 and 1.

Package updates

  • The documentation was updated to reflect the recent changes since scoringutils 1.1.0. In particular, usage of the functions set_forecast_unit(), check_forecasts() and transform_forecasts() are now documented in the Vignettes. The introduction of these functions enhances the overall workflow and help to make the code more readable. All functions are designed to be used together with the pipe operator. For example, one can now use something like the following:

example_quantile |> 
  set_forecast_unit(c("model", "location", "forecast_date", "horizon", "target_type")) |> 
  check_forecasts() |> 
  score()

Documentation for the transform_forecasts() has also been extended. This functions allows the user to easily add transformations of forecasts, as suggested in the paper “Scoring epidemiological forecasts on transformed scales”. In an epidemiological context, for example, it may make sense to apply the natural logarithm first before scoring forecasts, in order to obtain scores that reflect how well models are able to predict exponential growth rates, rather than absolute values. Users can now do something like the following to score a transformed version of the data in addition to the original one:


data <- example_quantile[true_value > 0, ]
data |>
  transform_forecasts(fun = log_shift, offset = 1) |> 
  score() |> 
  summarise_scores(by = c("model", "scale"))

Here we use the log_shift() function to apply a logarithmic transformation to the forecasts. This function was introduced in scoringutils 1.1.2 as a helper function that acts just like log(), but has an additional argument offset that can add a number to every prediction and observed value before applying the log transformation.

Feature updates

scoringutils 1.1.7

Release by @seabbs in #305. Reviewed by @nikosbosse and @sbfnk.

Breaking changes

  • The prediction_type argument of get_forecast_unit() has been changed dropped. Instead a new internal function prediction_is_quantile() is used to detect if a quantile variable is present. Whilst this is an internal function it may impact some users as it is accessible via `find_duplicates().

Package updates

Bug fixes

  • Fixed a bug in get_prediction_type() which led to it being unable to correctly detect integer (instead categorising them as continuous) forecasts when the input was a matrix. This issue impacted bias_sample() and also score() when used with integer forecasts resulting in lower bias scores than expected.

scoringutils 1.1.6

Feature updates

  • Added a new argument, across, to summarise_scores(). This argument allows the user to summarise scores across different forecast units as an alternative to specifying by. See the documentation for summarise_scores() for more details and an example use case.

scoringutils 1.1.5

Feature updates

  • Added a new function, set_forecast_unit() that allows the user to set the forecast unit manually. The function removes all columns that are not relevant for uniquely identifying a single forecast. If not done manually, scoringutils attempts to determine the unit of a single automatically by simply assuming that all column names are relevant to determine the forecast unit. This can lead to unexpected behaviour, so setting the forecast unit explicitly can help make the code easier to debug and easier to read (see issue #268). When used as part of a workflow, set_forecast_unit() can be directly piped into check_forecasts() to check everything is in order.

scoringutils 1.1.4

Package updates

scoringutils 1.1.3

Package updates

Package updates

  • Switched to a linting GitHub Action that only triggers on changes. Inspired by @bisaloo recent contribution to the epinowcast package.
  • Updated package linters to be more extensive. Inspired by @bisaloo recent contribution to the epinowcast package.
  • Resolved all flagged linting issues across the package.

scoringutils 1.1.2

Feature updates

scoringutils 1.1.1

  • Added a small change to interval_score() which explicitly converts the logical vector to a numeric one. This should happen implicitly anyway, but is now done explicitly in order to avoid issues that may come up if the input vector has a type that doesn’t allow the implicit conversion.

scoringutils 1.1.0

CRAN release: 2023-01-30

A minor update to the package with some bug fixes and minor changes.

Feature updates

Package updates

  • Removed the on attach message which warned of breaking changes in 1.0.0.
  • Renamed the metric argument of summarise_scores() to relative_skill_metric. This argument is now deprecated and will be removed in a future version of the package. Please use the new argument instead.
  • Updated the documentation for score() and related functions to make the soft requirement for a model column in the input data more explicit.
  • Updated the documentation for score(), pairwise_comparison() and summarise_scores() to make it clearer what the unit of a single forecast is that is required for computations
  • Simplified the function plot_pairwise_comparison() which now only supports plotting mean score ratios or p-values and removed the hybrid option to print both at the same time.

Bug fixes

  • Missing baseline forecasts in pairwise_comparison() now trigger an explicit and informative error message.
  • The requirements table in the getting started vignette is now correct.
  • Added support for an optional sample column when using a quantile forecast format. Previously this resulted in an error.

scoringutils 1.0.0

CRAN release: 2022-05-13

Major update to the package and most package functions with lots of breaking changes.

Feature updates

  • New and updated Readme and vignette.
  • The proposed scoring workflow was reworked. Functions were changed so they can easily be piped and have simplified arguments and outputs.

New functions and function changes

  • The function eval_forecasts() was replaced by a function score() with a much reduced set of function arguments.
  • Functionality to summarise scores and to add relative skill scores was moved to a function summarise_scores()
  • New function check_forecasts() to analyse input data before scoring
  • New function correlation() to compute correlations between different metrics
  • New function add_coverage() to add coverage for specific central prediction intervals.
  • New function avail_forecasts() allows to visualise the number of available forecasts.
  • New function find_duplicates() to find duplicate forecasts which cause an error.
  • All plotting functions were renamed to begin with plot_. Arguments were simplified.
  • The function pit() now works based on data.frames. The old pit function was renamed to pit_sample(). PIT p-values were removed entirely.
  • The function plot_pit() now works directly with input as produced by pit()
  • Many data-handling functions were removed and input types for score() were restricted to sample-based, quantile-based or binary forecasts.
  • The function brier_score() now returns all brier scores, rather than taking the mean before returning an output.
  • crps(), dss() and logs() were renamed to crps_sample(), dss_sample(), and logs_sample()

Bug fixes

Package data updated

  • Package data is now based on forecasts submitted to the European Forecast Hub (https://covid19forecasthub.eu/).
  • All example data files were renamed to begin with example_.
  • A new data set, summary_metrics was included that contains a summary of the metrics implemented in scoringutils.

Other breaking changes

  • The ‘sharpness’ component of the weighted interval score was renamed to dispersion. This was done to make it more clear what the component represents and to maintain consistency with what is used in other places.

scoringutils 0.1.8

Feature updates

  • Added a function check_forecasts() that runs some basic checks on the input data and provides feedback.

scoringutils 0.1.7.2

CRAN release: 2021-07-21

Package updates

  • Minor bug fixes (previously, ‘interval_score’ needed to be among the selected metrics).
  • All data.tables are now returned as table[] rather than as table, such that they don’t have to be called twice to display the contents.

scoringutils 0.1.7

CRAN release: 2021-07-14

Feature updates

  • Added a function, pairwise_comparison() that runs pairwise comparisons between models on the output of eval_forecasts()
  • Added functionality to compute relative skill within eval_forecasts().
  • Added a function to visualise pairwise comparisons.

Package updates

  • The WIS definition change introduced in version 0.1.5 was partly corrected such that the difference in weighting is only introduced when summarising over scores from different interval ranges.
  • “sharpness” was renamed to ‘mad’ in the output of [score()] for sample-based forecasts.

scoringutils 0.1.

Feature updates

  • eval_forecasts() can now handle a separate forecast and truth data set as as input.
  • eval_forecasts() now supports scoring point forecasts along side quantiles in a quantile-based format. Currently the only metric used is the absolute error.

Package updates

  • Many functions, especially eval_forecasts() got a major rewrite. While functionality should be unchanged, the code should now be easier to maintain
  • Some of the data-handling functions got renamed, but old names are supported as well for now.

scoringutils 0.1.5

Package updates

  • Changed the default definition of the weighted interval score. Previously, the median prediction was counted twice, but is no only counted once. If you want to go back to the old behaviour, you can call the interval_score function with the argument count_median_twice = FALSE.

scoringutils 0.1.4

CRAN release: 2020-11-17

Feature updates

  • Added basic plotting functionality to visualise scores. You can now easily obtain diagnostic plots based on scores as produced by score.
  • correlation_plot() shows correlation between metrics.
  • plot_ranges() shows contribution of different prediction intervals to some chosen metric.
  • plot_heatmap() visualises scores as heatmap.
  • plot_score_table() shows a coloured summary table of scores.

package updates

  • Renamed “calibration” to “coverage”.
  • Renamed “true_values” to “true_value” in data.frames.
  • Renamed “predictions” to “prediction” in data.frames.
  • Renamed “is_overprediction” to “overprediction”.
  • Renamed “is_underprediction” to “underprediction”.

scoringutils 0.1.3

(Potentially) Breaking changes

  • The by argument in score now has a slightly changed meaning. It now denotes the lowest possible grouping unit, i.e. the unit of one observation and needs to be specified explicitly. The default is now NULL. The reason for this change is that most metrics need scoring on the observation level and this the most consistent implementation of this principle. The pit function receives its grouping now from summarise_by. In a similar spirit, summarise_by has to be specified explicitly and e.g. doesn’t assume anymore that you want ‘range’ to be included.
  • For the interval score, weigh = TRUE is now the default option.
  • Renamed true_values to true_value and predictions to prediction.

Feature updates

  • Updated quantile evaluation metrics in score. Bias as well as calibration now take all quantiles into account.
  • Included option to summarise scores according to a summarise_by argument in score() The summary can return the mean, the standard deviation as well as an arbitrary set of quantiles.
  • score() can now return pit histograms.
  • Switched to ggplot2 for plotting.

scoringutils 0.1.2

(Potentially) Breaking changes

  • All scores in score were consistently renamed to lower case. Interval_score is now interval_score, CRPS is now crps etc.

Feature updates

  • Included support for grouping scores according to a vector of column names in score().
  • Included support for passing down arguments to lower-level functions in score()
  • Included support for three new metrics to score quantiles with score(): bias, sharpness and calibration

Package updates

  • Example data now has a horizon column to illustrate the use of grouping.
  • Documentation updated to explain the above listed changes.

scoringutils 0.1.1

Feature updates

  • Included support for a long as well as wide input formats for quantile forecasts that are scored with score().

Package updates

  • Updated documentation for the score().
  • Added badges to the README.