draw_from_posterior

Draw random numbers from posterior distribution

An implementation of a Bayesian framework for the opinion poll
based estimation of event probabilities in multi-party electoral systems
(Bender and Bauer (2018) <doi:10.21105/joss.00606>).

Andreas Bender

coalitions

Bayesian "Now-Cast" Estimation of Event Probabilities in
Multi-Party Democracies

Alexander Bauer

Rebekka Schade

draw_from_posterior function

<dl><dt>survey</dt>
<dd>survey object as returned by <code>as_survey</code> or <code>getSurveys</code></dd>
<dt>nsim</dt>
<dd>number of simulations</dd>
<dt>seed</dt>
<dd>sets seed</dd>
<dt>prior</dt>
<dd>optional prior information. Defaults to 1/2 (Jeffrey's prior).</dd>
<dt>correction</dt>
<dd>A positive number. If not <code>NULL</code>, each sample from the
Dirichlet distribution will be additionally "corrected" by a random number
from U(-1*correction, 1*correction). This can be used to introduce extra
variation which might be useful due to rounding errors from reported survey
results (or add an additional source of variation in general).</dd></dl>

Arguments

Draw random numbers from posterior distribution — draw_from_posterior

<dl>

<dt>survey</dt>
<dd>survey object as returned by <code>as_survey</code> or <code>getSurveys</code></dd>


<dt>nsim</dt>
<dd>number of simulations</dd>


<dt>seed</dt>
<dd>sets seed</dd>


<dt>prior</dt>
<dd>optional prior information. Defaults to 1/2 (Jeffrey's prior).</dd>


<dt>correction</dt>
<dd>A positive number. If not <code>NULL</code>, each sample from the
Dirichlet distribution will be additionally "corrected" by a random number
from U(-1*correction, 1*correction). This can be used to introduce extra
variation which might be useful due to rounding errors from reported survey
results (or add an additional source of variation in general).</dd>

</dl>

draw_from_posterior: Draw random numbers from posterior distribution

Description

Usage

Value

Arguments

See Also