Release CRAN v0.3.0 · tidyverts/fabletools

New features

Added scenarios() function for providing multiple scenarios to the
new_data argument. This allows different sets of future exogenous regressors
to be provided to functions like forecast(), generate(), and
interpolate() (#110).
Added quantile_score(), which is similar to percentile_score() except it
allows a set of quantile probs to be provided (#280).
Added distribution support for autoplot(<dable>). If the decomposition
provides distributions for its components, then the uncertainty of the
components will be plotted with interval ribbons.
Added block bootstrap option for bootstrapping innovations in generate().
Added multiple step ahead fitted values support via fitted(<mable>, h > 1).
Added as_fable(<forecast>) for converting older forecast class objects to
fable data structures.
Added top_down(method = "forecast_proportion") for reconciliation using the
forecast proportions techniques.
Added middle_out() forecast reconciliation method.
Added directional accuracy measures, including MDA(), MDV() and MDPV()
(#273, @davidtedfordholt).
Added fill_gaps(<fable>).

The pinball_loss() and percentile_score() accuracy measures are now scaled
up by 2x for improved meaning. The loss at 50% equals absolute error and the
average loss equals CRPS (#280).
Automatic transformation functions formals are now named after the response
variable and not converted to .x, preventing conflicts with values named .x.
box_cox() and inv_box_cox() are now vectorised over the transformation
parameter lambda.
RMSSE() accuracy measure is now included in default accuracy() measures.
Specifying a different response variable in as_fable() will no longer
error, it now sets the provided response value as the distribution's new
response.
Minor vctrs support improvements.