submesh

Remove part of a mesh without using INLA functions

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

submesh function

<dl><dt>mask</dt>
<dd>a 0-1 vector</dd>
<dt>mesh</dt>
<dd>a mesh resulting from a call to <code>make_mesh</code> with
<code>use_INLA = FALSE</code></dd></dl>

Arguments

Remove part of a mesh without using INLA functions — submesh

<dl>

<dt>mask</dt>
<dd>a 0-1 vector</dd>


<dt>mesh</dt>
<dd>a mesh resulting from a call to <code>make_mesh</code> with
<code>use_INLA = FALSE</code></dd>

</dl>

submesh: Remove part of a mesh without using INLA functions

Description

Usage

Value

Arguments