Thanks for all the replies.  I am passing along your comments to my
client but my job is just to find an easy way to implement orthogonal
L1 regression in C#.
I transcribed toms algorithm 478 (L1 optimization of a linear system
of equations) into C#, but it doesn't do orthogonal distance, so I am
following up with rotating the axes so that the hyperplane is
orthogonal to the "y" axis and trying again until the changes in the
parameters are small.  Problem is, things get unstable with more than
a few parameters, so I am using ad hoc methods to stop the params from
becoming huge.  That's hardly satisfying.

Any suggestions?

So, nobody tried to read the Bargiela/Hartley paper?

Vitaly
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