check_predictions

Helper function to check inputs for lower-level score functions.

internal

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

check_predictions function

<dl><dt>predictions</dt>
<dd>an object with predictions. Depending on whether
<code>class = vector</code> or <code>class = "matrix"</code> this can be either a vector of length
n (corresponding to the length of the true_values) or a nxN matrix of
predictive samples, n (number of rows) being the number of data points and
N (number of columns) the number of Monte Carlo samples</dd>
<dt>true_values</dt>
<dd>A vector with the true observed values of size n</dd>
<dt>type</dt>
<dd>character, one of "continuous" (default), "integer" or "binary" that
defines the type of the forecast</dd>
<dt>class</dt>
<dd>character, either "vector" (default) or "matrix" that determines the
class the input has to correspond to</dd></dl>

Arguments

Check Prediction Input For Lower-level Scoring Functions — check_predictions

<dl>

<dt>predictions</dt>
<dd>an object with predictions. Depending on whether
<code>class = vector</code> or <code>class = "matrix"</code> this can be either a vector of length
n (corresponding to the length of the true_values) or a nxN matrix of
predictive samples, n (number of rows) being the number of data points and
N (number of columns) the number of Monte Carlo samples</dd>


<dt>true_values</dt>
<dd>A vector with the true observed values of size n</dd>


<dt>type</dt>
<dd>character, one of "continuous" (default), "integer" or "binary" that
defines the type of the forecast</dd>


<dt>class</dt>
<dd>character, either "vector" (default) or "matrix" that determines the
class the input has to correspond to</dd>

</dl>

check_predictions: Check Prediction Input For Lower-level Scoring Functions

Description

Usage

Arguments