optim_doc: lm_svd_feasible

Next: residmin_stat, Previous: nonlin_curvefit, Up: Residual optimization [Index]

### 2.3 Default backend lm_svd_feasible of residual minimization

Levenberg/Marquardt algorithm using singular value decomposition. Constraints must be met by the initial parameters and are attempted to be kept met throughout the optimization.

Returned value cvg will be `0`, `1`, or `2`. Returned structure outp will have the fields `niter` and `user_interaction`.

Backend-specific defaults are: `MaxIter`: 20, `fract_prec`: `zeros (size (parameters))`, `max_fract_change`: `Inf` for all parameters. The setting `TolX` is not honoured.

Interpretation of `Display`: if set to `"iter"`, currently some diagnostics are printed.

Specific option: `lm_svd_feasible_alt_s`: if falling back to nearly gradient descent, do it more like original Levenberg/Marquardt method, with descent in each gradient component; for testing only.