check_input_point

Function assesses whether the inputs correspond to the
requirements for scoring point 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

check_input_point function

<dl><dt>observed</dt>
<dd>Input to be checked. Should be a numeric vector with the
observed values of size n.</dd>
<dt>predicted</dt>
<dd>Input to be checked. Should be a numeric vector with the
predicted values of size n.</dd></dl>

Arguments

Check that inputs are correct for point forecast — check_input_point

<dl>

<dt>observed</dt>
<dd>Input to be checked. Should be a numeric vector with the
observed values of size n.</dd>


<dt>predicted</dt>
<dd>Input to be checked. Should be a numeric vector with the
predicted values of size n.</dd>

</dl>

Check that inputs are correct for point forecast

check_input_point: Check that inputs are correct for point forecast

Description

Usage

Value

Arguments