nt_truncated_normal

Truncated Normally-Distributed Non-Decision Time

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

nt_truncated_normal function

<dl><dt>prms_model</dt>
<dd>the model parameters; including "non_dec" and
"sd_non_dec"</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

Truncated Normally-Distributed Non-Decision Time — nt_truncated_normal

<dl>

<dt>prms_model</dt>
<dd>the model parameters; including "non_dec" and
"sd_non_dec"</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>

nt_truncated_normal: Truncated Normally-Distributed Non-Decision Time

Description

Usage

Value

Arguments