parameters.emc

parameters

Returns a parameter type from an emc object as a data frame.

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

Raphael Hartmann

Karl C. Klauer

Steven G. Johnson

Jean M. Linhart

Brian Gough

Gerard Jungman

Rudolf Schuerer

Przemyslaw Sliwa

Jason H. Stover

parameters.emc function

<dl><dt>emc</dt>
<dd>An emc object</dd>
<dt>selection</dt>
<dd>String designating parameter type (e.g. mu, sigma2, correlation, alpha)</dd>
<dt>N</dt>
<dd>Integer. How many samples to take from the posterior. If <code>NULL</code> will return the full posterior</dd>
<dt>resample</dt>
<dd>Boolean. If <code>TRUE</code> will sample N samples from the posterior with replacement</dd>
<dt>...</dt>
<dd>Optional arguments that can be passed to <code>get_pars</code></dd></dl>

Arguments

Returns a parameter type from an emc object as a data frame. — parameters.emc

<dl>

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


<dt>selection</dt>
<dd>String designating parameter type (e.g. mu, sigma2, correlation, alpha)</dd>


<dt>N</dt>
<dd>Integer. How many samples to take from the posterior. If <code>NULL</code> will return the full posterior</dd>


<dt>resample</dt>
<dd>Boolean. If <code>TRUE</code> will sample N samples from the posterior with replacement</dd>


<dt>...</dt>
<dd>Optional arguments that can be passed to <code>get_pars</code></dd>

</dl>

Returns a parameter type from an emc object as a data frame.

parameters.emc: Returns a parameter type from an emc object as a data frame.

Description

Usage

Value

Arguments