scores_hyper

crps_hyper

logs_hyper

vector of observations / numbers of white balls drawn without replacement from an urn which contains both black and white balls.

the number of white balls in the urn.

the number of black balls in the urn.

the number of balls drawn from the urn, hence must be in
 \(0,1,\dots, m+n\).

Calculating scores for the hypergeometric distribution

Dictionary-like reference for computing scoring rules in a wide
range of situations. Covers both parametric forecast distributions (such as
mixtures of Gaussians) and distributions generated via simulation.

Fabian Krueger

scoringRules

Scoring Rules for Parametric and Simulated Distribution
Forecasts

scores_hyper function

<dl><dt>y</dt>
<dd>vector of observations / numbers of white balls drawn without replacement from an urn which contains both black and white balls.</dd>
<dt>m</dt>
<dd>the number of white balls in the urn.</dd>
<dt>n</dt>
<dd>the number of black balls in the urn.</dd>
<dt>k</dt>
<dd>the number of balls drawn from the urn, hence must be in
 \(0,1,\dots, m+n\).</dd></dl>

Arguments

Calculating scores for the hypergeometric distribution — scores_hyper

<dl>

<dt>y</dt>
<dd>vector of observations / numbers of white balls drawn without replacement from an urn which contains both black and white balls.</dd>


<dt>m</dt>
<dd>the number of white balls in the urn.</dd>


<dt>n</dt>
<dd>the number of black balls in the urn.</dd>


<dt>k</dt>
<dd>the number of balls drawn from the urn, hence must be in
 \(0,1,\dots, m+n\).</dd>

</dl>

scores_hyper: Calculating scores for the hypergeometric distribution

Description

Usage

Value

Arguments