Perhaps you can branch this code and improve it?

On Tue, Jun 11, 2013 at 2:43 PM, bthirion <notifications@github.com> wrote:

> In examples/ds105/ds105_example.py:
>
> > +
> > +    # Having estimated the random effects variance (and possibly smoothed it),
> > +    # the corresponding estimate of the effect and its variance is computed and
> > +    # saved.
> > +
> > +    # This is the coordmap we will use
> > +    coordmap = futil.load_image_fiac("fiac_00","wanatomical.nii").coordmap
> > +
> > +    adjusted_var = sd**2 + random_var
> > +    adjusted_sd = np.sqrt(adjusted_var)
> > +
> > +    results = onesample.estimate_mean(Y, adjusted_sd)
> > +    for n in ['effect', 'sd', 't']:
> > +        im = api.Image(results[n], copy(coordmap))
> > +        save_image(im, pjoin(odir, "%s.nii" % n))
> > +
>
> Note that The MLE for this mixed effects model has been implemented
> (actually twice).
> See nipy.algorithms.statistics.mixed_effects_stat.py
>
> —
> Reply to this email directly or view it on GitHub<https://github.com/nipy/nipy/pull/275/files#r4645774>
> .
>



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Jonathan Taylor
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