assert_input_nominal

Function assesses whether the inputs correspond to the
requirements for scoring nominal forecasts.

internal_input_check

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

assert_input_nominal function

<dl><dt>observed</dt>
<dd>Input to be checked. Should be an unordered factor of length
n with N levels holding the observed values. n is the number of
observations and N is the number of possible outcomes the observed values
can assume.</dd>
<dt>predicted</dt>
<dd>Input to be checked. Should be nxN matrix of predicted
probabilities, n (number of rows) being the number of data points and N
(number of columns) the number of possible outcomes the observed values
can assume.
If <code>observed</code> is just a single number, then predicted can just be a
vector of size N.
Values represent the probability that the corresponding value
in <code>observed</code> will be equal to the factor level referenced in
<code>predicted_label</code>.</dd>
<dt>predicted_label</dt>
<dd>Unordered factor of length N with N levels, where N
is the number of possible outcomes the observed values can assume.</dd></dl>

Arguments

Assert that inputs are correct for nominal forecasts — assert_input_nominal

<dl>

<dt>observed</dt>
<dd>Input to be checked. Should be an unordered factor of length
n with N levels holding the observed values. n is the number of
observations and N is the number of possible outcomes the observed values
can assume.</dd>


<dt>predicted</dt>
<dd>Input to be checked. Should be nxN matrix of predicted
probabilities, n (number of rows) being the number of data points and N
(number of columns) the number of possible outcomes the observed values
can assume.
If <code>observed</code> is just a single number, then predicted can just be a
vector of size N.
Values represent the probability that the corresponding value
in <code>observed</code> will be equal to the factor level referenced in
<code>predicted_label</code>.</dd>


<dt>predicted_label</dt>
<dd>Unordered factor of length N with N levels, where N
is the number of possible outcomes the observed values can assume.</dd>

</dl>

Assert that inputs are correct for nominal forecasts

assert_input_nominal: Assert that inputs are correct for nominal forecasts

Description

Usage

Value

Arguments