NLFitLevenbergMarquardtFit(NLFitLMFunction, Double, Double, Double, CancellationToken, Int32) Method | 
             The purpose of LevenbergMarquardtFit is to minimize the sum of the
             squares of m nonlinear functions in n variables by a modification of the
             Levenberg-Marquardt algorithm. This is done by using the more
             general least-squares solver below. The user must provide a
             subroutine which calculates the functions. The Jacobian is
             then calculated by a forward-difference approximation.
             
Namespace: Altaxo.Calc.RegressionAssembly: AltaxoCore (in AltaxoCore.dll) Version: 4.8.3261.0 (4.8.3261.0)
Syntaxpublic static void LevenbergMarquardtFit(
	NLFitLMFunction fcn,
	double[] xvec,
	double[] fvec,
	double tol,
	CancellationToken cancellationToken,
	ref int info
)
Parameters
- fcn  NLFitLMFunction
 - The user supplied function which provides the values to minimize.
 - xvec  Double
 - 
             Array of length n containing the parameter vector. On input x must contain
             an initial estimate of the solution vector. On output x
             contains the final estimate of the solution vector.
             
 - fvec  Double
 - Output array of length m which contains the functions evaluated at the output x. 
 - tol  Double
 - 
             Nonnegative input variable. Termination occurs
             when the algorithm estimates either that the relative
             error in the sum of squares is at most tol or that
             the relative error between x and the solution is at
             most tol.
             
 - cancellationToken  CancellationToken
 - Token to cancel the fit.
 - info  Int32
 - 
             Info is an integer output variable. If the user has
             terminated execution, info is set to the (negative)
             value of iflag. See description of fcn. Otherwise,
             info is set as follows:
            
                     info = 0  improper input parameters.
            
                     info = 1  algorithm estimates that the relative error
                               in the sum of squares is at most tol.
            
                     info = 2  algorithm estimates that the relative error
                               between x and the solution is at most tol.
            
                     info = 3  conditions for info = 1 and info = 2 both hold.
            
                     info = 4  fvec is orthogonal to the columns of the
                               Jacobian to machine precision.
            
                     info = 5  number of calls to fcn has reached or
                               exceeded 200*(n+1).
            
                     info = 6  tol is too small. No further reduction in
                               the sum of squares is possible.
            
                     info = 7  tol is too small. No further improvement in
                               the approximate solution x is possible.
             
 
Remarks
             This is the most easy-to-use interface with the smallest number of
             arguments. If you need more control over the minimization process and
             auxilliary storage allocation you should use one of the interfaces
             described below.
             
See Also