Making joint simulations, went back to cholesky.  Made 'niceDTImodel' for cholesky starting points.
Fixed bug in starting point for dti to note the chol() returns upper diag, not lower diag.  Power calc test now is on reasonable ranges for both snr and lambda ratio.
Removed iteration constraints.  Wroking on making it faster.
I looked at the setup for 'approxchol', where I convert the regression starting point X into a positive definite by trying to take the approxiamte cholesky decomposition.  I had been using the identity matrix when X was negative definite.  I replaced this with an upper diagonal with 1 on the diag and randoms on the off-diags, and this worked.  I think feeding the algorithm anything with zeros cuased it to go haywire.
Earlier the chol was throwing an error, which gave me 99s.  Now it's running through the alg and crashing it again.
Contains changes from Friday.
I just rewrote EllipsoidModel and it now works.  Documentation is in the notes.  Slightly concerning: the p values I'm seeing now reject constants in favor of isotropy, fail to reject isotropy for an ellipsoid, and then reject ellipsoids for tensors...
Fixed EllipsoidModel.  Everything works now.
Merge branch 'backtocholesky'