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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.