supported_models

Measurement models available in <code>bmm</code>

Fit computational and measurement models using full Bayesian
inference. The package provides a simple and accessible interface by
translating complex domain-specific models into 'brms' syntax, a
powerful and flexible framework for fitting Bayesian regression models
using 'Stan'. The package is designed so that users can easily apply
state-of-the-art models in various research fields, and so that
researchers can use it as a new model development framework.
References: Frischkorn and Popov (2023) <doi:10.31234/osf.io/umt57>.

Vencislav Popov

Easy and Accessible Bayesian Measurement Models Using 'brms'

Gidon T. Frischkorn

Paul-Christian Bürkner

supported_models function

<dl><dt>print_call</dt>
<dd>Logical; If TRUE (default), the function will print
information about how each model function should be called and its required
arguments. If FALSE, the function will return a character vector with the
names of the available models</dd></dl>

Arguments

Measurement models available in bmm — supported_models

<dl>

<dt>print_call</dt>
<dd>Logical; If TRUE (default), the function will print
information about how each model function should be called and its required
arguments. If FALSE, the function will return a character vector with the
names of the available models</dd>

</dl>

supported_models: Measurement models available in `bmm`

Description

Usage

Value

Arguments

Examples