Changelog • hubEvals

hubEvals (development version)

score_model_out() now returns a tibble (inheriting from scoringutils’ scores class) instead of a data.table. This gives more predictable user-facing behaviour (e.g. with $ access, printing, and dplyr) while keeping the scores class so downstream scoringutils helpers like get_metrics() continue to work (#70).
score_model_out() now errors when no requested metric produces a score.
Fix transform_quantile_model_out(), transform_point_model_out(), and transform_sample_model_out() to handle oracle outputs that carry an output_type_id column without an output_type column. Previously, this combination caused as_forecast_*() to error on a stray output_type_id (#73).

Add support for scoring sample output types via transform_sample_model_out() and the "sample" case in score_model_out(). Marginal scoring produces metrics such as CRPS, bias, and DSS; compound scoring (via the new compound_taskid_set argument) produces multivariate scores such as energy score and variogram score for joint forecasts (#94).
score_model_out() now errors with a clear message when a scale transformation produces non-finite values (NaN or Inf), instead of silently returning invalid scores (#99).

Add transform, transform_append, and transform_label arguments to score_model_out() for computing scores on transformed scales (e.g., log, sqrt). Supported for quantile, mean, and median output types (#48, #91).

Export functions transform_pmf_model_out(), transform_point_model_out(), and transform_quantile_model_out() used to transform hubverse model outputs into a scoringutils forecast object
Update package dependencies to use CRAN releases when available
Update README to include simple examples of package functions