ensure_mv_grouping

Shared helper for multivariate forecast constructors. Applies
<code>set_grouping()</code> when <code>joint_across</code> is provided, or checks that
<code>.mv_group_id</code> already exists.

internal

Facilitate the evaluation of forecasts in a convenient
framework based on data.table. It allows user to to check their forecasts
and diagnose issues, to visualise forecasts and missing data, to transform
data before scoring, to handle missing forecasts, to aggregate scores, and
to visualise the results of the evaluation. The package mostly focuses on
the evaluation of probabilistic forecasts and allows evaluating several
different forecast types and input formats. Find more information about the
package in the Vignettes as well as in the accompanying paper,
<doi:10.48550/arXiv.2205.07090>.

Nikos Bosse

scoringutils

Utilities for Scoring and Assessing Predictions

Sam Abbott

Hugo Gruson

Johannes Bracher

Toshiaki Asakura 

James Mba Azam

Sebastian Funk

Michael Chirico

ensure_mv_grouping function

<dl><dt>data</dt>
<dd>A data.frame (or similar) with predicted and observed values.
See the "Target format" section in Details for additional information
on the required input format.</dd>
<dt>joint_across</dt>
<dd>Character vector with columns names that define the
variables which are forecasted jointly. Conceptually, several univariate
forecasts are pooled together to form a single multivariate forecasts.
For example, if you have a column <code>country</code> and want to define
a multivariate forecast for several countries at once, you could set
<code>joint_across = "country"</code>.</dd></dl>

Arguments

Ensure multivariate grouping is set — ensure_mv_grouping

<dl>

<dt>data</dt>
<dd>A data.frame (or similar) with predicted and observed values.
See the "Target format" section in Details for additional information
on the required input format.</dd>


<dt>joint_across</dt>
<dd>Character vector with columns names that define the
variables which are forecasted jointly. Conceptually, several univariate
forecasts are pooled together to form a single multivariate forecasts.
For example, if you have a column <code>country</code> and want to define
a multivariate forecast for several countries at once, you could set
<code>joint_across = "country"</code>.</dd>

</dl>

Ensure multivariate grouping is set

ensure_mv_grouping: Ensure multivariate grouping is set

Description

Usage

Value

Arguments