quantile_example_data_plain

A toy dataset for quantile forecasts of an outcome variable in a format
that uses plain quantiles instead of interval ranges

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_plain function

A data frame with 600 rows and 6 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 horzin (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>quantile</dt><dd>quantile of the corresponding prediction</dd>
</dl>

Format

Quantile Example Data - Plain Quantile Format — quantile_example_data_plain

A data frame with 600 rows and 6 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 horzin (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>quantile</dt><dd>quantile of the corresponding prediction</dd>
</dl>

quantile_example_data_plain: Quantile Example Data - Plain Quantile Format

Description

Usage

Arguments

Format