simulateBrains: A function for simulating PET data
In julia-wrobel/depthTests: Nonparametric Tests for Images based on Band Depth

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