internal_aggregate

internal function to aggregate columns of a data frame across "ID"
while considering a set of grouping columns. It retains the class and
attriubtes of the input data.

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

internal_aggregate function

<dl><dt>data</dt>
<dd>A <a href="/link/data.frame?package=dRiftDM&version=0.3.1" data-mini-rdoc="dRiftDM::data.frame">data.frame</a> containing the data to be aggregated. It should
include both the grouping columns, an "ID" column, and the columns for which
aggregation shall take place.</dd>
<dt>group_cols</dt>
<dd>A character vector specifying the names of the columns to
group by during aggregation.</dd></dl>

Arguments

Aggregate Data Frame Columns by Group — internal_aggregate

<dl>

<dt>data</dt>
<dd>A <a href='https://rdrr.io/r/base/data.frame.html'>data.frame</a> containing the data to be aggregated. It should
include both the grouping columns, an "ID" column, and the columns for which
aggregation shall take place.</dd>


<dt>group_cols</dt>
<dd>A character vector specifying the names of the columns to
group by during aggregation.</dd>

</dl>

internal_aggregate: Aggregate Data Frame Columns by Group

Description

Usage

Value

Arguments

Details

See Also