Not sure if anyone has the code pre-compiled, but all you need is:

xX.xKXs   = spm_sp('Set',spm_filter(xX.K,W*xX.X));       % KWX

xX.xKXs.X = full(xX.xKXs.X);

xX.pKX    = spm_sp('x-',xX.xKXs); 

KWY   = spm_filter(xX.K,W*Y);

beta  = xX.pKX*KWY;


Hope this helps.


Best Regards, Donald McLaren
=================
D.G. McLaren, Ph.D.
Research Fellow, Department of Neurology, Massachusetts General Hospital and
Harvard Medical School
Postdoctoral Research Fellow, GRECC, Bedford VA
Website: http://www.martinos.org/~mclaren
Office: (773) 406-2464
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On Tue, Jan 28, 2014 at 12:35 PM, Bruno L. Giordano <[log in to unmask]> wrote:
Hello,

I am planning to run some permutation analysis by permuting condition labels in the first-level model.

I wonder whether someone managed to hack the first-level model routines so that they take in input and give in output variables stored in the workspace rather than stored on the disk (I would actually need only the parameter estimates, and not the stats, which should make things much easier). I suspect that in the case of a permutation analysis disk access is going to be a considerable limiting factor for the speed of the computations, and I wouldn't like to overload the parallel grid with unnecessary overheads.

Thank you for any tip.

        Bruno

~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Bruno L. Giordano, PhD
Institute of Neuroscience and Psychology
58 Hillhead Street, University of Glasgow
Glasgow, G12 8QB, Scotland
T +44 (0) 141 330 5484
Www: http://www.brunolgiordano.net