init_objfn

Objective function for the initialization of kappa2 and phi

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

init_objfn function

<dl><dt>theta</dt>
<dd>a vector c(kappa2,phi)</dd>
<dt>spde</dt>
<dd>an spde object</dd>
<dt>beta_hat</dt>
<dd>vector</dd></dl>

Arguments

Objective function for the initialization of kappa2 and phi — init_objfn

<dl>

<dt>theta</dt>
<dd>a vector c(kappa2,phi)</dd>


<dt>spde</dt>
<dd>an spde object</dd>


<dt>beta_hat</dt>
<dd>vector</dd>

</dl>

init_objfn: Objective function for the initialization of kappa2 and phi

Description

Usage

Value

Arguments