Re: minpack code for least squares?

[Olaf Till]

> Further, MINPACK's LMDER and LMDIF are likely the most widely used
> nonlinear least-squares codes in history, so they're sort of "proven
> quality".

'leasqr' (m-code, in 'optim') also provides an l/m-algorithm,
optionally with user-supplied jacobian. Seems to work well, we had
problems in which it did converge, though Matlabs 'lsqcurvefit'
l/m-method only pretended to and lingered at the starting values. It
should be tested carefully if 'lmder' and 'lmdif' are indeed
better. Even in this case I would vote to have the 'leasqr' code kept
in place.

Olaf