plot_mcmc

Uses the coda plot functions that are applied per chain

Fit Bayesian (hierarchical) cognitive models
using a linear modeling language interface using particle metropolis Markov
chain Monte Carlo sampling with Gibbs steps. The diffusion decision model (DDM),
linear ballistic accumulator model (LBA), racing diffusion model (RDM), and the lognormal
race model (LNR) are supported. Additionally, users can specify their own likelihood
function and/or choose for non-hierarchical
estimation, as well as for a diagonal, blocked or full multivariate normal
group-level distribution to test individual differences. Prior specification
is facilitated through methods that visualize the (implied) prior.
A wide range of plotting functions assist in assessing model convergence and
posterior inference. Models can be easily evaluated using functions
that plot posterior predictions or using relative model comparison metrics
such as information criteria or Bayes factors.
References: Stevenson et al. (2024) <doi:10.31234/osf.io/2e4dq>.

Niek Stevenson

EMC2

Bayesian Hierarchical Analysis of Cognitive Models of Choice

Michelle Donzallaz

Andrew Heathcote

Steven Miletić

Jochen Voss

Andreas Voss

plot_mcmc function

<dl><dt>emc</dt>
<dd>An emc object</dd>
<dt>selection</dt>
<dd>A Character string. Indicates which parameter type to plot (e.g., <code>alpha</code>, <code>mu</code>, <code>sigma2</code>, <code>correlation</code>).</dd>
<dt>fun</dt>
<dd>A plot function that takes a vector/mcmc object as input, e.g. cumuplot, acf</dd>
<dt>layout</dt>
<dd>A vector indicating which layout to use as in par(mfrow = layout). If NA, will automatically generate an appropriate layout.</dd>
<dt>chain</dt>
<dd>Integer, which chain to include, if more than 1 will make separate plots per chain.</dd>
<dt>plot_type</dt>
<dd>type argument passed on to coda fun.</dd>
<dt>...</dt>
<dd>Optional arguments that can be passed to <code>get_pars</code>,
the chosen coda plot function, or <code>plot.default</code> (see <code><a href="/link/par()?package=EMC2&version=2.0.2" data-mini-rdoc="EMC2::par()">par()</a></code>)</dd></dl>

Arguments

Plot MCMC — plot_mcmc

<dl>

<dt>emc</dt>
<dd>An emc object</dd>


<dt>selection</dt>
<dd>A Character string. Indicates which parameter type to plot (e.g., <code>alpha</code>, <code>mu</code>, <code>sigma2</code>, <code>correlation</code>).</dd>


<dt>fun</dt>
<dd>A plot function that takes a vector/mcmc object as input, e.g. cumuplot, acf</dd>


<dt>layout</dt>
<dd>A vector indicating which layout to use as in par(mfrow = layout). If NA, will automatically generate an appropriate layout.</dd>


<dt>chain</dt>
<dd>Integer, which chain to include, if more than 1 will make separate plots per chain.</dd>


<dt>plot_type</dt>
<dd>type argument passed on to coda fun.</dd>


<dt>...</dt>
<dd>Optional arguments that can be passed to <code>get_pars</code>,
the chosen coda plot function, or <code>plot.default</code> (see <code><a href='https://rdrr.io/r/graphics/par.html'>par()</a></code>)</dd>

</dl>

plot_mcmc: Plot MCMC

Description

Usage

Value

Arguments