fabletools 0.7.0

New features

• Added coherent_smat() and coherent_cmat() for obtaining the structural and
  zero-constraint matrices that encode the coherency structure of related time
  series (#429).

Improvements

• Added the preferred mdl_lst class to the previously named lst_mdl class
  for consistency with other model list classes mdl_df and mdl_ts (#433).
• Added mdl_lst methods for augment(), glance(), and tidy() to enable global models (including reconciliation models) to
  provide statistics for these methods (#424).
• Added warning for hfitted() used on models without refit() method (#432).

fabletools 0.6.1

Small patch to progress deprecation of graphics functionality that required updating reverse dependencies to require fabletools >=0.6.0.

Breaking changes

• The autoplot() and autolayer() methods for graphics functions now require the fabletools to be attached (not just loaded). If you previously used library() to load fabletools (or fable, fpp3), your code will continue to work. We do however recommend that you also include library(ggtime) (or fpp3) for time-series graphics going forward.

fabletools 0.6.0

This release migrates graphics functionality to {ggtime}. The commonly used graphics functions are currently exported with a soft deprecation message. To use the autoplot() and autolayer() time series plot helper functions please include library(ggtime) in your code.

After a (very) gradual deprecation process, the {ggtime} dependency will be removed and the graphics functions will stop being re-exported. This deprecation process is planned to span approximately 2 years, after which explicitly using {ggtime} will be required.

Improvements

• Update for compatibility with distributional v0.6.0.
• Documentation improvements.

CRAN v0.5.1

Compatibility release for upcoming ggplot2 4.0.0 release.

Bug fixes

• Fixed forecast autoplot() and autolayer() draw key for single-point
  multiple-forecast ribbons (#414).
• Fixed issue with accuracy(<fbl_ts>) when not all key variables were
  specified in by (#421).

CRAN v0.5.0

New features

• Added the IRF() generic and appropriate mable methods for computing
  impulse response functions from fitted models.
• It is now possible to generate() bootstrap sample paths for
  multivariate models.

Improvements

• Added support for multivariate model forecasting with transformation using
  sample paths.
• Performance improvements relating to forecasting with transformations and
  sample paths.
• Forecast plots now explicitly use marginal distributions for plotting
  forecast intervals from multivariate distributions.
• Added optional progress reporting when producing forecasts, it can be
  enabled using progressr::with_progress()

Bug fixes

• Fixed issue with autoplot() and length 1 forecasts (#400).

CRAN v0.4.1

Minor patch for upcoming release of ggdist v3.3.1

Improvements

• Added (scaled) pinball loss metrics to interval_accuracy_measures (#379).
• Improved use of random seed in parallel modelling and forecasting (#384).
• Documentation improvements

CRAN v0.4.0

Improvements

• Improved handling of combination_model() when used with transformed
  component models.
• autoplot(<fbl_ts>), autolayer(<fbl_ts>) and autoplot(<dcmp_ts>) now use
  the ggdist package visualising uncertainty with distributional vectors.

CRAN v0.3.4

fabletools 0.3.4

New features

• The formula parser now identifies and stores length 1 values in the
  transformation environment. This simplifies common tasks like automatic
  box-cox parameters for each series, which can now be done with
  fable::ARIMA(box_cox(y, feasts::guerrero(y))).

Improvements

• Added support for visualising different point forecasts (say means and medians)
  when only one forecast is to be plotted for each series.

Bug fixes

• Resolved issue with autoplot(<fbl_ts>) not identifying multiple point
  forecasts by linetype.
• Fix for indexing of bottom series in top_down() and middle_out()
  reconciliation methods (#362, #364 @federicogarza)

CRAN v0.3.3

fabletools 0.3.3

Improvements

• Fixed handling of transformed distributions which accept a parameter from the
  dataset.
• . in a model formula for xreg implemented with special_xreg() will now
  include all measured variables (excluding the index and key variables).
• Improved handling of transformations with forecast sample distributions.
• Added support for reconciling sample paths.
• accuracy(<fbl_ts>) can now summarise accuracy over key variables. This is
  done by specifying the accuracy by argument and not including some (or all)
  of the fable's key variables (#341).
• Like forecast(), generate() will now keep exogenous regressors in the
  output table.
• Re-export generics::forecast() for better compatibility with registering
  methods alongside other packages (#375).

CRAN v0.3.2

fabletools 0.3.2

New features

• Added hypothesize() generic for running statistical tests on a trained model.
• Added combination_weighted() function for producing a combination model with
  arbitrary weights.

Improvements

• The fallback residuals() method now handles transformations when
  type = "innovation".
• Improved supported expressions for producing combination models. The
  appropriate response variable is now simplified for all functions that produce
  that original response variable. This notably includes 0.7*mdl1 + 0.3*mdl2 -
  if mdl1 and mdl2 are models with the same response variables, then the
  resulting combination model will also have the same response variable.
• Documentation improvements.

Bug fixes

• Fixed issue with exogenous regressors (xreg) in reconciliation methods that
  partially forecast the hierarchy.
• Fixed issue with keys being dropped when several mdl_df (mable) objects were
  combined.