Efficient method to perform a simple linear regression across dimensions
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I have a 4D array of neuroimaging data (nSubj*x*y*z), and a 2D array of covariates (nSubj*1).
What is an efficient way to do a separate regression for every voxel (i.e. value of x, y, and z) to the array of covariates, resulting in a 3D array of regression values (size=x*y*z)?
Thanks!
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Star Strider
2015-11-22
0 个投票
The best I can do is to direct you to the general section in the Statistics Toolbox documentation on Linear Regression and let you explore. I cannot suggest anything specific, because I’m not certain what you’re doing.
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