A nonlinear least squares solver with \(n\) model parameters and \(m\) observations.  
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#include <dumux/nonlinear/leastsquares.hh>
template<class 
Assembler, class 
LinearSolver>
class Dumux::Optimization::Detail::LevenbergMarquardt< Assembler, LinearSolver >
- Template Parameters
- 
  
    | Assembler | a class that assembles the linear system of equations in each iteration |  | LinearSolver | a class that solves the linear system of equations |  
 
- Note
- The assembler has to assemble the actual least squares problem (i.e. the normal equations) 
|  | 
| void | newtonEndStep (Variables &vars, const SolutionVector &uLastIter) override | 
|  | 
| void | lineSearchUpdate_ (Variables &vars, const SolutionVector &uLastIter, const ResidualVector &deltaU) override | 
|  | 
| bool | apply (Variables &vars) override | 
|  | Run the Newton method to solve a non-linear system. The solver is responsible for all the strategic decisions. 
 | 
|  | 
| virtual void | newtonEndStep (Variables &vars, const SolutionVector &uLastIter) | 
|  | Indicates that one Newton iteration was finished. 
 | 
|  | 
◆ LevenbergMarquardt()
◆ apply()
- Parameters
- 
  
    | vars | instance of the Variablesclass representing a numerical solution, defining primary and possibly secondary variables and information on the time level. |  
 
- Returns
- bool true if the solver converged 
- Postcondition
- If converged, the given Variableswill represent the solution. If the solver does not converge, theVariableswill represent the best solution so far (lowest value of the objective function)
 
 
◆ lineSearchUpdate_()
◆ newtonEndStep()
The documentation for this class was generated from the following file: