Click or drag to resize

Altaxo.Calc.Optimization.ObjectiveFunctions Namespace

[Missing <summary> documentation for "N:Altaxo.Calc.Optimization.ObjectiveFunctions"]

Classes
 ClassDescription
Public classForwardDifferenceGradientObjectiveFunction Adapts an objective function with only value implemented to provide a gradient as well. Gradient calculation is done using the finite difference method, specifically forward differences. For each gradient computed, the algorithm requires an additional number of function evaluations equal to the functions's number of input parameters.
Public classLazyObjectiveFunctionBase 
Public classNonlinearObjectiveFunctionNonAllocating Non-allocating nonlinear objective function implementation wrapping user-provided model and (optionally) derivative delegates.
Public classNonlinearObjectiveFunctionNonAllocatingBase Base implementation for a nonlinear objective model that supports allocation-free evaluation for Levenberg-Marquardt-style algorithms.
Public classObjectiveFunctionBase