dt_b_constant

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

dt_b_constant function

<dl><dt>prms_model</dt>
<dd>the model parameters, no prm label required</dd>
<dt>prms_solve</dt>
<dd>solver settings</dd>
<dt>t_vec</dt>
<dd>time space</dd>
<dt>one_cond</dt>
<dd>one condition</dd>
<dt>ddm_opts</dt>
<dd>optional arguments attached to an object</dd></dl>

Arguments

Derivative of a Constant Boundary — dt_b_constant

<dl>

<dt>prms_model</dt>
<dd>the model parameters, no prm label required</dd>


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


<dt>t_vec</dt>
<dd>time space</dd>


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


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

</dl>

dt_b_constant: Derivative of a Constant Boundary

Description

Usage

Value

Arguments