非线性优化-matlab函数库-optimset

创建或编辑一个最优化参数选项

句法规则

options = optimset('param1',value1,'param2',value2,...) %设置所有参数及其值，未设置的为默认值

options = optimset(optimfun)                                        %设置与最优化函数有关的参数为默认
options = optimset(oldopts,'param1',value1,...)             %复制一个已存在的选项，修改特定项
options = optimset(oldopts,newopts)                            %用另一个新选项合并目前选项因素

Parameter	Value	Description
Display	'off' | 'iter' | 'final' | 'notify'	'off' 表示不显示输出; 'iter' 显示每次迭代的结果; 'final' 只显示最终结果; 'notify' 只在函数不收敛的时候显示结果.
MaxFunEvals	positive integer	函數求值運算（Function Evaluation）的最高次數
MaxIter	positive integer	最大疊代次數.
TolFun	positive scalar	函数迭代的终止误差.
TolX	positive scalar	结束迭代的X值.

L - 只用于大规模数据拟合 
M - 中等规模 
B - 两者都可以 

Parameter Name	Description	L, M, B	Used by Functions
DerivativeCheck	Compare user-supplied analytic derivatives (gradients or Jacobian) to finite differencing derivatives.	M	fgoalattain, fmincon,fminimax, fminunc, fseminf,fsolve, lsqcurvefit, lsqnonlin
Diagnostics	Print diagnostic information about the function to be minimized or solved.	B	All but fminbnd,fminsearch, fzero, andlsqnonneg
DiffMaxChange	Maximum change in variables for finite difference derivatives.	M	fgoalattain, fmincon,fminimax, fminunc, fseminf,fsolve, lsqcurvefit, lsqnonlin
DiffMinChange	Minimum change in variables for finite difference derivatives.	M	fgoalattain, fmincon,fminimax, fminunc, fseminf,fsolve, lsqcurvefit, lsqnonlin
Display	Level of display. 'off' displays no output; 'iter' displays output at each iteration; 'final' displays just the final output; 'notify' displays output only if function does not converge.	B	All. See the individual function reference pages for the values that apply.
GoalsExactAchieve	Number of goals to achieve exactly (do not over- or underachieve).	M	fgoalattain
GradConstr	Gradients for the nonlinear constraints defined by the user.	M	fgoalattain, fmincon,fminimax
GradObj	Gradient(s) for the objective function(s) defined by the user.	B	fgoalattain, fmincon,fminimax, fminunc, fseminf
Hessian	If 'on', function uses user-defined Hessian, or Hessian information (when using HessMult), for the objective function. If 'off', function approximates the Hessian using finite differences.	L	fmincon, fminunc
HessMult	Hessian multiply function defined by the user.	L	fmincon, fminunc,quadprog
HessPattern	Sparsity pattern of the Hessian for finite differencing. The size of the matrix is n-by-n, where n is the number of elements in x0, the starting point.	L	fmincon, fminunc
HessUpdate	Quasi-Newton updating scheme.	M	fminunc
Jacobian	If 'on', function uses user-defined Jacobian, or Jacobian information (when using JacobMult), for the objective function. If 'off', function approximates the Jacobian using finite differences.	B	fsolve, lsqcurvefit,lsqnonlin
JacobMult	Jacobian multiply function defined by the user.	L	fsolve, lsqcurvefit, lsqlin,lsqnonlin
JacobPattern	Sparsity pattern of the Jacobian for finite differencing. The size of the matrix is m-by-n, where m is the number of values in the first argument returned by the user-specified function fun, and n is the number of elements in x0, the starting point.	L	fsolve, lsqcurvefit,lsqnonlin
LargeScale	Use large-scale algorithm if possible.	B	fmincon, fminunc,fsolve, linprog, lsqcurvefit,lsqlin, lsqnonlin, quadprog
LevenbergMarquardt	Chooses Levenberg-Marquardt over Gauss-Newton algorithm.	M	lsqcurvefit, lsqnonlin
LineSearchType	Line search algorithm choice.	M	fminunc, fsolve,lsqcurvefit, lsqnonlin
MaxFunEvals	Maximum number of function evaluations allowed.	B	fgoalattain, fminbnd,fmincon, fminimax,fminsearch, fminunc,fseminf, fsolve, lsqcurvefit,lsqnonlin
MaxIter	Maximum number of iterations allowed.	B	All but fzero andlsqnonneg
MaxPCGIter	Maximum number of PCG iterations allowed.	L	fmincon, fminunc,fsolve, lsqcurvefit, lsqlin,lsqnonlin, quadprog
MeritFunction	Use goal attainment/minimax merit function (multiobjective) vs. fmincon (single objective).	M	fgoalattain, fminimax
MinAbsMax	Number of F(x) to minimize the worst case absolute values	M	fminimax
NonlEqnAlgorithm	Choose Levenberg-Marquardt or Gauss-Newton over the trust-region dogleg algorithm.	M	fsolve
PrecondBandWidth	Upper bandwidth of preconditioner for PCG.	L	fmincon, fminunc,fsolve, lsqcurvefit, lsqlin,lsqnonlin, quadprog
TolCon	Termination tolerance on the constraint violation.	B	fgoalattain, fmincon,fminimax, fseminf
TolFun	Termination tolerance on the function value.	B	fgoalattain, fmincon,fminimax, fminsearch,fminunc, fseminf, fsolve,linprog (large-scale only),lsqcurvefit, lsqlin (large-scale only), lsqnonlin,quadprog (large-scale only)
TolPCG	Termination tolerance on the PCG iteration.	L	fmincon, fminunc,fsolve, lsqcurvefit, lsqlin,lsqnonlin, quadprog
TolX	Termination tolerance on x.	B	All functions except the medium-scale algorithms forlinprog, lsqlin, and quadprog
TypicalX	Typical x values. The length of the vector is equal to the number of elements in x0, the starting point.	L	fmincon, fminunc,fsolve, lsqcurvefit, lsqlin,lsqnonlin, quadprog

Examples

options = optimset('Display','iter','TolFun',1e-8)

This statement makes a copy of the options structure called options, changing the value of the TolX parameter and storing new values in optnew.

·                optnew = optimset(options,'TolX',1e-4);

 

This statement returns an optimization options structure that contains all the parameter names and default values relevant to the function fminbnd.

·                optimset('fminbnd')

转：https://blog.csdn.net/listener51/article/details/25164847?utm_source=blogxgwz18

一般常用的LM最小二乘拟合设置：
错误

optimset('LevenbergMarquardt','on','LargeScale','off');
正确

options = optimset('Display','off','TolX',eps,'TolFun',eps,'LargeScale','on',...
   'Algorithm','Levenberg-Marquardt');
转：https://blog.csdn.net/u012319493/article/details/77801454?utm_source=blogxgwz13