Description Usage Arguments Author(s)
View source: R/simulateBrains.R
This function takes a PCA decomposition of a PET dataset and simulates new images.
1 2 | simulateBrains(PCAobject, npixels = 7505, npc = NULL, pve = 0.95,
nsubjs = 30, scoreMean = 0, muScale = 1, muShift = 0, varscale = 1)
|
PCAobject |
The PCA breakdown of either your test or control data. Needs to be formatted as a list with eigenvalues as evalues, eigenvectors as 'efunctions', and mean vector as 'mean' |
npixels |
The number of pixels in your original image. Defaults to 7505, the number of pixels in provided pet2D data. |
npc |
Number of principal components to use for simulating data. Defaults to NULL. |
pve |
Percent Variance explained by PCA decomposition. Defaults to 0.95. |
nsubjs |
The number of images you want to simulate. |
scoreMean |
The mean score for the simulated subjects. |
muScale |
A constant multiplier which scales the mean image. |
muShift |
A constant for shifting the mean image. |
varscale |
A constant multiplier for increasing the variance of all eigenvalues |
Julia Wrobel jw3134@cumc.columbia.edu
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