quantile_example_data_long

A toy dataset for quantile forecasts of an outcome variable

datasets

Combines a collection of metrics and proper scoring rules
(Tilmann Gneiting & Adrian E Raftery (2007)
<doi:10.1198/016214506000001437>) with an easy to
use wrapper that can be used to automatically evaluate predictions.
Apart from proper scoring rules functions are provided to assess bias,
sharpness and calibration (Sebastian Funk, Anton Camacho, Adam J. Kucharski,
Rachel Lowe, Rosalind M. Eggo, W. John Edmunds (2019)
<doi:10.1371/journal.pcbi.1006785>) of forecasts.
Several types of predictions can be evaluated:
probabilistic forecasts (generally
predictive samples generated by Markov Chain Monte Carlo procedures),
quantile forecasts or point forecasts. Observed values and predictions
can be either continuous, integer, or binary. Users can either choose
to apply these rules separately in a vector / matrix format that can
be flexibly used within other packages, or they can choose to do an
automatic evaluation of their forecasts. This is implemented with
'data.table' and provides a consistent and very efficient framework for
evaluating various types of predictions.

Nikos Bosse

scoringutils

Utilities for Scoring and Assessing Predictions

Sam Abbott 

Joel Hellewell

Sophie Meakins 

James Munday

Katharine Sherratt

Sebastian Funk

quantile_example_data_long function

A data frame with 720 rows and 7 variables:<dl class="dl-horizontal">
 <dt>true_value</dt><dd>true observed values</dd>
 <dt>id</dt><dd>unique identifier for true observed values</dd>
 <dt>horizon</dt><dd>forecast horizon (e.g. 1 day ahead forecast)</dd>
 <dt>model</dt><dd>name of the model that generated the forecasts</dd>
 <dt>prediction</dt><dd>quantile predictions</dd>
 <dt>boundary</dt><dd>lower or upper bound of an interval range</dd>
 <dt>range</dt><dd>interval range for which the quantile forecast was made</dd>
</dl>

Format

Quantile Example Data - Long Format — quantile_example_data_long

A data frame with 720 rows and 7 variables:<dl class='dl-horizontal'>
 <dt>true_value</dt><dd>true observed values</dd>
 <dt>id</dt><dd>unique identifier for true observed values</dd>
 <dt>horizon</dt><dd>forecast horizon (e.g. 1 day ahead forecast)</dd>
 <dt>model</dt><dd>name of the model that generated the forecasts</dd>
 <dt>prediction</dt><dd>quantile predictions</dd>
 <dt>boundary</dt><dd>lower or upper bound of an interval range</dd>
 <dt>range</dt><dd>interval range for which the quantile forecast was made</dd>
</dl>

quantile_example_data_long: Quantile Example Data - Long Format

Description

Usage

Arguments

Format