.initialKP

Find the initial values of kappa2 and phi

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

.initialKP function

<dl><dt>theta</dt>
<dd>a vector of length two containing the range and scale parameters
kappa2 and phi, in that order</dd>
<dt>spde</dt>
<dd>a list containing the sparse matrix elements Cmat, Gmat, and GtCinvG</dd>
<dt>w</dt>
<dd>the beta_hat estimates for a single task</dd>
<dt>n_sess</dt>
<dd>the number of sessions</dd>
<dt>tol</dt>
<dd>the stopping rule tolerance</dd>
<dt>verbose</dt>
<dd>(logical) Should intermediate output be displayed?</dd></dl>

Arguments

Find the initial values of kappa2 and phi — .initialKP

<dl>

<dt>theta</dt>
<dd>a vector of length two containing the range and scale parameters
kappa2 and phi, in that order</dd>


<dt>spde</dt>
<dd>a list containing the sparse matrix elements Cmat, Gmat, and GtCinvG</dd>


<dt>w</dt>
<dd>the beta_hat estimates for a single task</dd>


<dt>n_sess</dt>
<dd>the number of sessions</dd>


<dt>tol</dt>
<dd>the stopping rule tolerance</dd>


<dt>verbose</dt>
<dd>(logical) Should intermediate output be displayed?</dd>

</dl>

.initialKP: Find the initial values of kappa2 and phi

Description

Usage

Arguments