calc_cafs_obs

calc_cafs_pred

Backend functions to calculate conditional accuracy functions for RT
vectors or pdfs

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

calc_cafs_obs function

<dl><dt>rts_u, rts_l</dt>
<dd>vectors of RTs for the upper and lower boundary</dd>
<dt>one_cond</dt>
<dd>character label</dd>
<dt>n_bins</dt>
<dd>number of bins to use for the CAFs</dd>
<dt>pdf_u, pdf_l</dt>
<dd>density values for the upper and lower boundary</dd>
<dt>t_vec</dt>
<dd>the time space</dd></dl>

Arguments

Calculate CAFs — calc_cafs_obs

<dl>

<dt>rts_u, rts_l</dt>
<dd>vectors of RTs for the upper and lower boundary</dd>


<dt>one_cond</dt>
<dd>character label</dd>


<dt>n_bins</dt>
<dd>number of bins to use for the CAFs</dd>


<dt>pdf_u, pdf_l</dt>
<dd>density values for the upper and lower boundary</dd>


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

</dl>

calc_cafs_obs: Calculate CAFs

Description

Usage

Value

Arguments

Details