[pymvpa] effect of signal on null distributions

[J.A. Etzel]

I posted images of some of the null distributions I get after changing 
the simulation code here: 
http://mvpa.blogspot.com/2013/02/comparing-null-distributions-changing_15.html 
- they now look a lot closer to Yaroslav and Michael's examples (though 
not exactly the same - I used different voxel counts, all voxels have 
the signal, etc.).

So how we simulate the data really matters, more than I'd guessed.

Do these conclusions seem sensible to all of you? Has anyone been able 
to take a look at the questions?

thanks,
Jo


On 2/13/2013 5:06 PM, J.A. Etzel wrote:
> Two questions:
> Does my description seem accurate for normal_feature_dataset? In
> particular, do you set the class B values as class A / snr, or generate
> a separate set of normal values for A and B, then divide the B values?
>
> What do the null distribution for different amounts of signal look like
> if you try the simulations making the data as I describe (values from
> two normal distributions with a small difference in mean but same
> standard deviation)?

-- 
Joset A. Etzel, Ph.D.
Research Analyst
Cognitive Control & Psychopathology Lab
Washington University in St. Louis
http://mvpa.blogspot.com/