plot.bayes_mixture

Plot an estimated mixture for a given number of draws with a frequency distribution of the data.

A two-step Bayesian approach for mode inference following
Cross, Hoogerheide, Labonne and van Dijk (2024) <doi:10.1016/j.econlet.2024.111579>).
First, a mixture distribution is fitted on the data using a sparse finite
mixture (SFM) Markov chain Monte Carlo (MCMC) algorithm. The number of
mixture components does not have to be known; the size of the mixture is
estimated endogenously through the SFM approach. Second, the modes of the
estimated mixture at each MCMC draw are retrieved using algorithms
specifically tailored for mode detection. These estimates are then used to
construct posterior probabilities for the number of modes, their locations
and uncertainties, providing a powerful tool for mode inference.

Paul Labonne

BayesMultiMode

Bayesian Mode Inference

Nalan Baştürk

Jamie Cross

Peter de Knijff

Lennart Hoogerheide

Herman van Dijk

plot.bayes_mixture function

<dl><dt>x</dt>
<dd>An object of class <code>bayes_mixture</code>.</dd>
<dt>draws</dt>
<dd>The number of MCMC draws to plot.</dd>
<dt>draw</dt>
<dd>Plot estimated mixture in draw <code>draw</code>; note that <code>draws</code> is discarded. Default is <code>NULL</code>.</dd>
<dt>bins</dt>
<dd>(for continuous mixtures) Number of bins for the histogram of
the data. Passed to <code>geom_histogram()</code>.</dd>
<dt>alpha</dt>
<dd>transparency of the density lines. Default is 0.1. Should be greater than 0 and below or equal to 1.</dd>
<dt>...</dt>
<dd>Not used.</dd></dl>

Arguments

Plot method for bayes_mixture objects — plot.bayes_mixture

<dl>

<dt>x</dt>
<dd>An object of class <code>bayes_mixture</code>.</dd>


<dt>draws</dt>
<dd>The number of MCMC draws to plot.</dd>


<dt>draw</dt>
<dd>Plot estimated mixture in draw <code>draw</code>; note that <code>draws</code> is discarded. Default is <code>NULL</code>.</dd>


<dt>bins</dt>
<dd>(for continuous mixtures) Number of bins for the histogram of
the data. Passed to <code>geom_histogram()</code>.</dd>


<dt>alpha</dt>
<dd>transparency of the density lines. Default is 0.1. Should be greater than 0 and below or equal to 1.</dd>


<dt>...</dt>
<dd>Not used.</dd>

</dl>

plot.bayes_mixture: Plot method for `bayes_mixture` objects

Description

Usage

Arguments