stats_from_pdfs_agg_info

Internal helper to compute predicted summary statistics from condition-wise
PDFs, following the condition order. Calculates summary
statistics according to the information in <code>stats_agg_info</code>. Currently
supports either quantiles or conditional accuracy functions (CAFs).

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

stats_from_pdfs_agg_info function

<dl><dt>pdfs</dt>
<dd>named list of PDFs per condition, each containing elements
<code>pdf_u</code> and <code>pdf_l</code>.</dd>
<dt>t_vec</dt>
<dd>numeric time vector.</dd>
<dt>dt</dt>
<dd>numeric time step.</dd>
<dt>stats_agg_info</dt>
<dd>list with information needed to compute summaries
(e.g., quantile probabilities or CAF bin counts; optional).</dd>
<dt>what</dt>
<dd>character, one of <code>"quantiles"</code> or <code>"cafs"</code>, selecting which
statistic to compute.</dd></dl>

Arguments

Get Quantiles/CAFs from PDFs and stats_agg_info — stats_from_pdfs_agg_info

<dl>

<dt>pdfs</dt>
<dd>named list of PDFs per condition, each containing elements
<code>pdf_u</code> and <code>pdf_l</code>.</dd>


<dt>t_vec</dt>
<dd>numeric time vector.</dd>


<dt>dt</dt>
<dd>numeric time step.</dd>


<dt>stats_agg_info</dt>
<dd>list with information needed to compute summaries
(e.g., quantile probabilities or CAF bin counts; optional).</dd>


<dt>what</dt>
<dd>character, one of <code>"quantiles"</code> or <code>"cafs"</code>, selecting which
statistic to compute.</dd>

</dl>

stats_from_pdfs_agg_info: Get Quantiles/CAFs from PDFs and stats_agg_info

Description

Usage

Value

Arguments