Solve an unconstrained optimization problem defined by the function fcn.
fcn should accept a vector (array) defining the unknown variables, and
return the objective function value, optionally with gradient.
fminunc
attempts to determine a vector x such that
fcn (x)
is a local minimum.
x0 determines a starting guess. The shape of x0 is preserved in all calls to fcn, but otherwise is treated as a column vector.
options is a structure specifying additional options. Currently,
fminunc
recognizes these options:
"FunValCheck"
, "OutputFcn"
, "TolX"
,
"TolFun"
, "MaxIter"
, "MaxFunEvals"
,
"GradObj"
, "FinDiffType"
, "TypicalX"
,
"AutoScaling"
.
If "GradObj"
is "on"
, it specifies that fcn, when
called with two output arguments, also returns the Jacobian matrix of
partial first derivatives at the requested point. TolX
specifies
the termination tolerance for the unknown variables x, while
TolFun
is a tolerance for the objective function value fval.
The default is 1e-7
for both options.
For a description of the other options, see optimset
.
On return, x is the location of the minimum and fval contains the value of the objective function at x.
info may be one of the following values:
Converged to a solution point. Relative gradient error is less than
specified by TolFun
.
Last relative step size was less than TolX
.
Last relative change in function value was less than TolFun
.
Iteration limit exceeded—either maximum number of algorithm iterations
MaxIter
or maximum number of function evaluations MaxFunEvals
.
Algorithm terminated by OutputFcn
.
The trust region radius became excessively small.
Optionally, fminunc
can return a structure with convergence
statistics (output), the output gradient (grad) at the
solution x, and approximate Hessian (hess) at the solution
x.
Application Notes: If the objective function is a single nonlinear equation
of one variable then using fminbnd
is usually a better choice.
The algorithm used by fminunc
is a gradient search which depends
on the objective function being differentiable. If the function has
discontinuities it may be better to use a derivative-free algorithm such as
fminsearch
.
See also: fminbnd, fminsearch, optimset.
Package: octave