ar_smooth_Param

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

ar_smooth_Param function

<dl><dt>ar_smooth</dt>
<dd>(numeric) FWHM parameter for smoothing the AR model
coefficient estimates for prewhitening. Remember that
\(\sigma = \frac{FWHM}{2*sqrt(2*log(2)}\). Set to <code>0</code> or <code>NULL</code>
to not do any smoothing. Default: <code>5</code>.</dd></dl>

Arguments

ar_smooth — ar_smooth_Param

<dl>

<dt>ar_smooth</dt>
<dd>(numeric) FWHM parameter for smoothing the AR model
coefficient estimates for prewhitening. Remember that
\(\sigma = \frac{FWHM}{2*sqrt(2*log(2)}\). Set to <code>0</code> or <code>NULL</code>
to not do any smoothing. Default: <code>5</code>.</dd>

</dl>

ar_smooth

ar_smooth_Param: ar_smooth

Description

Arguments