Sim.3D.GRF {AnalyzeFMRI} | R Documentation |
Simulates a Gaussian Random Field with specified dimensions and covariance structure.
Sim.3D.GRF(d, voxdim, sigma, ksize, mask = NULL, type = c("field", "max"))
d |
A vector specifying the dimensions of a 3D or 4D array. |
voxdim |
The dimensions of each voxel. |
sigma |
The 3D covariance matrix of the field. |
ksize |
The size (in voxels) of the kernel with which to filter the independent field. |
mask |
A 3D mask for the field. |
type |
If type == "field" then the simulated field together with the maximum of the field is returned. If type == "max" then the maximum of the field is returned. |
The function works by simulating a Gaussian r.v at each voxel location and then smoothing the field with a discrete filter to obtain a field with the desired covariance structure.
mat |
Contains the simulated field if type == "field", else NULL |
max |
The maximum value of the simulated field. |
J. L. Marchini
GaussSmoothArray
,GaussSmoothKernel
d <- c(64, 64, 21) FWHM <- 9 sigma <- diag(FWHM^2, 3) / (8 * log(2)) voxdim <- c(2, 2, 4) msk <- array(1, dim = d) field <- Sim.3D.GRF(d = d, voxdim = voxdim, sigma = sigma, ksize = 9, mask = msk, type = "max")