trim_INLA_model_obj

Trim an INLA object to only include what is necessary for
<code>id_activations</code> or <code>BayesGLM2</code>.

internal

Performs a spatial Bayesian general linear model (GLM) for task
functional magnetic resonance imaging (fMRI) data on the cortical surface.
Additional models include group analysis and inference to detect thresholded
areas of activation. Includes direct support for the 'CIFTI' neuroimaging
file format. For more information see A. F. Mejia, Y. R. Yue, D. Bolin, F.
Lindgren, M. A. Lindquist (2020) <doi:10.1080/01621459.2019.1611582> and D.
Spencer, Y. R. Yue, D. Bolin, S. Ryan, A. F. Mejia (2022)
<doi:10.1016/j.neuroimage.2022.118908>.

Amanda Mejia

BayesfMRI

Spatial Bayesian Methods for Task Functional MRI Studies

Daniel Spencer

Damon Pham

David Bolin

Sarah Ryan

Yu (Ryan) Yue

trim_INLA_model_obj function

<dl><dt>INLA_model_obj</dt>
<dd>An object of class <code>"inla"</code>.</dd>
<dt>minimal</dt>
<dd>Just keep the two parameters needed for <code>BayesGLM2</code>?
Default: <code>FALSE</code>. <code>!minimal</code> is required for
<code>id_activations</code>, but <code>minimal</code> is sufficient for
<code>BayesGLM2</code>.</dd></dl>

Arguments

Trim INLA object — trim_INLA_model_obj

<dl>

<dt>INLA_model_obj</dt>
<dd>An object of class <code>"inla"</code>.</dd>


<dt>minimal</dt>
<dd>Just keep the two parameters needed for <code>BayesGLM2</code>?
Default: <code>FALSE</code>. <code>!minimal</code> is required for
<code>id_activations</code>, but <code>minimal</code> is sufficient for
<code>BayesGLM2</code>.</dd>

</dl>

trim_INLA_model_obj: Trim INLA object

Description

Usage

Value

Arguments