pw_estimate

Estimate residual autocorrelation for prewhitening

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

pw_estimate function

<dl><dt>resids</dt>
<dd>Estimated residuals</dd>
<dt>ar_order, aic</dt>
<dd>Order of the AR model used to prewhiten the data at each location.
If <code>!aic</code> (default), the order will be exactly <code>ar_order</code>. If <code>aic</code>,
the order will be between zero and <code>ar_order</code>, as determined by the AIC.</dd></dl>

Arguments

Estimate residual autocorrelation for prewhitening — pw_estimate

<dl>

<dt>resids</dt>
<dd>Estimated residuals</dd>


<dt>ar_order, aic</dt>
<dd>Order of the AR model used to prewhiten the data at each location.
If <code>!aic</code> (default), the order will be exactly <code>ar_order</code>. If <code>aic</code>,
the order will be between zero and <code>ar_order</code>, as determined by the AIC.</dd>

</dl>

pw_estimate: Estimate residual autocorrelation for prewhitening

Description

Usage

Value

Arguments