waveletcoef.Rdwaveletcoef applies DWT to a 2D GLM coefficient map (e.g., corresponding to a single brain slice) of a regressor for each subject, and returns the wavelet coefficients at all resolution levels. This function wraps around the wavelet transformation function imwd of the wavethresh package.
waveletcoef(n, grid, glmcoefstd, wave.family="DaubLeAsymm",
filter.number=6, bc="periodic")Number of subjects.
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 grid^2. The maximum value of grid for this package is 512.
An array of dimension (n,grid,grid), containing for each subject the standardized GLM coefficients of a regressor obtained by fitting GLM to the time-series corresponding to the voxels.
The family of wavelets to use - "DaubExPhase" or "DaubLeAsymm". Default is "DaubLeAsymm".
The number of vanishing moments of the wavelet. Default is 6.
The boundary condition to use - "periodic" or "symmetric". Default is "periodic".
A list containing the following.
A matrix of dimension (n,grid^2-1), containing for each subject the wavelet coefficients of all levels stacked together (by the increasing order of resolution level).
The wavelet decomposition is performed by using the function imwd.
set.seed(1)
n <- 3
grid <- 8
ntime <- 10
designmat <- cbind( rep(1,10), c(rep(c(1,0),5)) )
data <- array(dim=c(n,grid,grid,ntime),
rnorm(n*grid*grid*ntime))
glm.fit <- glmcoef(n,grid,data,designmat)
#> Error in glmcoef_sub(grid, data[i, , , ], designmat): object '_BHMSMAfMRI_glmcoef_sub' not found
glmcoefstd <- glm.fit$GLMCoefStandardized[,,,1]
#> Error in glm.fit$GLMCoefStandardized: object of type 'closure' is not subsettable
wavecoef <- waveletcoef(n,grid,glmcoefstd)
#> Error in eval(expr, envir, enclos): object 'glmcoefstd' not found
dim(wavecoef$WaveletCoefficientMatrix)
#> Error in eval(expr, envir, enclos): object 'wavecoef' not found
#[1] 3 63