Changes in version 0.3.0 (2026-06-29)                  

  - score_model_out() now handles single-model input gracefully when
    relative metrics are requested. Previously this errored via
    scoringutils ("not enough comparators"); now the relative-skill
    columns are filled with 1, matching the trivial fact that a model
    has skill 1 relative to itself. If a baseline is supplied that does
    not match the lone model, score_model_out() errors with a clear
    message (#75).

  - New "Getting started with hubEvals" vignette walking through the
    main scoring workflows for each supported output type (quantile,
    mean, median, pmf nominal/ordinal, sample marginal/compound), the
    relative_metrics and baseline arguments for relative-skill scoring,
    and the transform and transform_append arguments for scoring on
    transformed scales (#38).

  - Fix score_model_out() so that requesting transform_append = TRUE
    with default summarize = TRUE now correctly returns one row per
    scale (natural and transformed) per model, instead of silently
    averaging across scales (#122).

  - score_model_out() now errors with a clear hubEvals message when
    "bias" is requested as a relative metric, instead of letting
    scoringutils fail downstream with a cryptic "all values must have
    the same sign" error. Bias is a signed quantity, so a geometric-mean
    pairwise ratio has no clean interpretation (#119).

  - 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).

                        Changes in version 0.2.0                        

  - 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).

                        Changes in version 0.1.0                        

  - 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).

                        Changes in version 0.0.1                        

  - 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

                     Changes in version 0.0.0.9001                      

  - Add score_model_out() function for evaluating model outputs
  - Add tests to package
  - Update organisation name to hubverse-org

                     Changes in version 0.0.0.9000                      

  - Initial package dev setup.