find_duplicates

Helper function to identify duplicate forecasts, i.e.
instances where there is more than one forecast for the same prediction
target.

check-forecasts

Provides a collection of metrics and proper scoring rules
(Tilmann Gneiting & Adrian E Raftery (2007)
<doi:10.1198/016214506000001437>, Jordan, A., Krüger, F., & Lerch, S. (2019)
<doi:10.18637/jss.v090.i12>) within a consistent framework for
evaluation, comparison and visualisation of forecasts.
In addition to 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 (e.g. binary, discrete, continuous) which may
come in different formats (e.g. forecasts represented by predictive samples
or by quantiles of the predictive distribution) can be evaluated.
Scoring metrics can be used either through a convenient data.frame format,
or can be applied as individual functions in a vector / matrix format.
All functionality has been implemented with a focus on performance and is
robustly tested. Find more information about the package 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 

Sebastian Funk

find_duplicates function

<dl><dt>data</dt>
<dd>A data.frame as used for <code>score()</code></dd>
<dt>forecast_unit</dt>
<dd>A character vector with the column names that define
the unit of a single forecast. If missing the function tries to infer the
unit of a single forecast.</dd></dl>

Arguments

Find duplicate forecasts — find_duplicates

<dl>

<dt>data</dt>
<dd>A data.frame as used for <code>score()</code></dd>


<dt>forecast_unit</dt>
<dd>A character vector with the column names that define
the unit of a single forecast. If missing the function tries to infer the
unit of a single forecast.</dd>

</dl>

find_duplicates: Find duplicate forecasts

Description

Usage

Value

Arguments

Examples