postgroupglmcoef | R Documentation |
postgroupglmcoef
computes posterior group mean (or group median) of a 2D GLM coefficients map (e.g., corresponding to a single brain slice) of a regressor using the posterior means (or medians) of the corresponding wavelet coefficients from all subjects in the inverse discrete wavelet transform based on multi-subject or single subject analyses (see References).
postgroupglmcoef( n, grid, glmcoefstd, postmeanwaveletcoef,
wave.family="DaubLeAsymm", filter.number=6, bc="periodic" )
n |
Number of subjects. |
grid |
The number of voxels in one row (or, one column) of the brain slice of interest. Must be a power of 2. The total number of voxels is |
glmcoefstd |
An array of dimension |
postmeanwaveletcoef |
A matrix of size |
wave.family |
The family of wavelets to use - "DaubExPhase" or "DaubLeAsymm". Default is "DaubLeAsymm". |
filter.number |
The number of vanishing moments of the wavelet. Default is 6. |
bc |
The boundary condition to use - "periodic" or "symmetric". Default is "periodic". |
The wavelet transformation and reconstruction are performed by using the functions imwd
and imwr
, respectively.
A list containing the following.
groupcoef |
A matrix of dimension (grid, grid), containing the posterior group coefficients obtained by BHMSMA methodology. |
Nilotpal Sanyal, Marco Ferreira
Maintainer: Nilotpal Sanyal <nilotpal.sanyal@gmail.com>
Sanyal, Nilotpal, and Ferreira, Marco A.R. (2012). Bayesian hierarchical multi-subject multiscale analysis of functional MRI data. Neuroimage, 63, 3, 1519-1531.
readfmridata
, glmcoef
, postglmcoef
, postwaveletcoef
, substituteWaveletCoef
, imwd
, imwr
set.seed(1)
n <- 3
grid <- 8
glmcoefstd <- array(rnorm(n*grid*grid),
dim=c(n,grid,grid))
postmeanwaveletcoef <- array(rnorm(n*(grid^2-1)),
dim=c(n,grid^2-1))
post.groupcoef <- postgroupglmcoef(n,grid,glmcoefstd,
postmeanwaveletcoef)
dim(post.groupcoef$groupcoef)
#[1] 8 8
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