get_posterior_densities2

Extracts posterior density estimates for hyperparameters for volumetric SPDE

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

Damon Pham

David Bolin

Yu (Ryan) Yue

Daniel Spencer

Sarah Ryan

get_posterior_densities2 function

<dl><dt>INLA_model_obj</dt>
<dd>An object of class <code>"inla"</code>, a result of a call to
<code>inla()</code></dd>
<dt>field_names</dt>
<dd>Descriptive names of model regressors (fields).</dd></dl>

Arguments

This function requires the <code>INLA</code> package, which is not a CRAN package.
See <a href="https://www.r-inla.org/download-install">https://www.r-inla.org/download-install</a> for easy installation instructions.

INLA Requirement

Extracts posterior density estimates for hyperparameters for volumetric SPDE — get_posterior_densities2

<dl>

<dt>INLA_model_obj</dt>
<dd>An object of class <code>"inla"</code>, a result of a call to
<code>inla()</code></dd>


<dt>field_names</dt>
<dd>Descriptive names of model regressors (fields).</dd>

</dl>

This function requires the <code>INLA</code> package, which is not a CRAN package.
See <a href='https://www.r-inla.org/download-install'>https://www.r-inla.org/download-install</a> for easy installation instructions.

get_posterior_densities2: Extracts posterior density estimates for hyperparameters for volumetric SPDE

Description

Usage

Value

Arguments

INLA Requirement