get_subset_chains

When calling <code>estimate_bayesian()</code>, the MCMC results are
packed up as an <code>mcmc_dm</code> object. This function is used in the depths of
<code>dRiftDM</code> to extract the relevant array of MCMC samples,
depending on whether the model is hierarchical and whether a participant ID
is provided.

internal

Fit and explore Drift Diffusion Models (DDMs),
a common tool in psychology for describing decision processes in simple
tasks. It can handle both time-independent and time-dependent DDMs. You
either choose prebuilt models or create your own, and the package takes
care of model predictions and parameter estimation. Model predictions
are derived via the numerical solutions provided by Richter, Ulrich, and
Janczyk (2023, <doi:10.1016/j.jmp.2023.102756>).

Valentin Koob

dRiftDM

Estimating (Time-Dependent) Drift Diffusion Models

Thomas Richter

Markus Janczyk

get_subset_chains function

<dl><dt>chains_obj</dt>
<dd>an object of class<code>mcmc_dm</code>.</dd>
<dt>id</dt>
<dd>an optional single numeric or character, specifying the <code>ID</code> of a
participant to extract individual-level samples from a hierarchical model.
Ignored for non-hierarchical models.</dd></dl>

Arguments

Extract a Subset of MCMC Chains — get_subset_chains

<dl>

<dt>chains_obj</dt>
<dd>an object of class<code>mcmc_dm</code>.</dd>


<dt>id</dt>
<dd>an optional single numeric or character, specifying the <code>ID</code> of a
participant to extract individual-level samples from a hierarchical model.
Ignored for non-hierarchical models.</dd>

</dl>

get_subset_chains: Extract a Subset of MCMC Chains

Description

Usage

Value

Arguments