uniMCMCResults

<p>Results from a univariate Metropolis-Hastings algorithm run on a tri-modal posterior.
Although the standard traceplot and Gelman-Rubin diagnostic show good mixing, the results
are actually mixing poorly. Included for examples.</p>

datasets

Trace plots and convergence diagnostics for Markov Chain Monte Carlo (MCMC) algorithms on highly multivariate or unordered spaces. Methods outlined in a forthcoming paper.

Luke Duttweiler

genMCMCDiag

Generalized Convergence Diagnostics for Difficult MCMC
Algorithms

uniMCMCResults function


<div class="section" id="unimcmcresults">
<h3><code>uniMCMCResults</code></h3><p></p><p>
</p><p>A list with 7 elements, each representing a different MCMC chain. Each element is
a numeric vector of length 2000</p>
</div>


Format

Results from a univariate MCMC algorithm on a simulated posterior — uniMCMCResults


<div class='section' id='unimcmcresults'>
<h3><code>uniMCMCResults</code></h3>


<p>A list with 7 elements, each representing a different MCMC chain. Each element is
a numeric vector of length 2000</p>
</div>


uniMCMCResults: Results from a univariate MCMC algorithm on a simulated posterior

Description

Usage

Arguments

Format

`uniMCMCResults`