x_beta

Beta-Shaped Starting Point Distribution Centered Around Zero

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

x_beta function

<dl><dt>prms_model</dt>
<dd>the model parameters; prm name "alpha" required</dd>
<dt>prms_solve</dt>
<dd>solver settings</dd>
<dt>x_vec</dt>
<dd>evidence space</dd>
<dt>one_cond</dt>
<dd>one condition</dd>
<dt>ddm_opts</dt>
<dd>optional arguments attached to an object</dd></dl>

Arguments

Beta-Shaped Starting Point Distribution Centered Around Zero — x_beta

<dl>

<dt>prms_model</dt>
<dd>the model parameters; prm name "alpha" required</dd>


<dt>prms_solve</dt>
<dd>solver settings</dd>


<dt>x_vec</dt>
<dd>evidence space</dd>


<dt>one_cond</dt>
<dd>one condition</dd>


<dt>ddm_opts</dt>
<dd>optional arguments attached to an object</dd>

</dl>

x_beta: Beta-Shaped Starting Point Distribution Centered Around Zero

Description

Usage

Value

Arguments