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@mitchelloharawild mitchelloharawild released this 19 Jan 11:43
v0.2.1
3370168

New features

  • Added bottom_up() forecast reconciliation method.
  • Added the skill_score() accuracy measure modifier.
  • Added agg_vec() for manually producing aggregation vectors.

Improvements

  • Fixed some inconsistencies in key ordering of model accessors (such as
    augment(), tidy() and glance()) with model methods (such as forecast()
    and generate()).
  • Improved equality comparison of agg_vec classes, aggregated values will now
    always match regardless of the value used.
  • Using summarise() with a fable will now retain the fable class if the
    distribution still exists under the same variable name.
  • Added as_fable.forecast() to convert forecast objects from the forecast
    package to work with fable.
  • Improved CRPS() performance when using sampling distributions (#240).
  • Reconciliation now works with hierarchies containing aggregate leaf nodes,
    allowing unbalanced hierarchies to be reconciled.
  • Produce unique names for unnamed features used with features() (#258).
  • Documentation improvements
  • Performance improvements, including using future.apply() to parallelize
    forecast() when the future package is attached (#268).

Breaking changes

  • The residuals obtained from the augment() function are no longer controlled
    by the type argument. Response residuals (y - yhat) are now always found
    in the .resid column, and innovation residuals (the model's error) are now
    found in the .innov column. Response residuals will differ from innovation
    residuals when transformations are used, and if the model has non-additive
    residuals.
  • dist_*() functions are now removed, and are completely replaced by the
    distributional package. These are removed to prevent masking issues when
    loading packages.
  • fortify(<fable>) will now return a tibble with the same structure as the
    fable, which is more useful for plotting forecast distributions with the
    ggdist package. It can no longer be used to extract intervals from the
    forecasts, this can be done using hilo(), and numerical values from a
    <hilo> can be extracted with unpack_hilo() or interval$lower.

Bug fixes

  • Fixed issue with aggregated date vectors (#230).
  • Fixed display of models in View() panel.
  • Fixed issue with combination models not inheriting vctrs functionality (#237).
  • aggregate_key() can now be used with non-syntactic variable names.
  • Added tsibble cast methods for fable and dable objects, fixing issues with
    tidyverse functionality between datasets of different column orders (#247).
  • Fixed refit() dropping reconciliation attributes (#251).
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