MultiFunctionMathFindLocalMinimum Method (FuncIReadOnlyListDouble, Double, IReadOnlyListDouble, MultiExtremumSettings)

public static MultiExtremum FindLocalMinimum(
	Func<IReadOnlyList<double>, double> function,
	IReadOnlyList<double> start,
	MultiExtremumSettings settings
)

Public Shared Function FindLocalMinimum ( 
	function As Func(Of IReadOnlyList(Of Double), Double),
	start As IReadOnlyList(Of Double),
	settings As MultiExtremumSettings
) As MultiExtremum

public:
static MultiExtremum^ FindLocalMinimum(
	Func<IReadOnlyList<double>^, double>^ function, 
	IReadOnlyList<double>^ start, 
	MultiExtremumSettings^ settings
)

static member FindLocalMinimum : 
        function : Func<IReadOnlyList<float>, float> * 
        start : IReadOnlyList<float> * 
        settings : MultiExtremumSettings -> MultiExtremum 

Parameters

function

Type: SystemFuncIReadOnlyListDouble, Double
The multi-dimensional function to minimize.

start

Type: System.Collections.GenericIReadOnlyListDouble
The starting location for the search.

settings

Type: Meta.Numerics.AnalysisMultiExtremumSettings
The evaluation settings that govern the search for the minimum.

Return Value

The Hessian (matrix of second derivatives) returned with the minimum is an approximation that is constructed in the course of search. It should be considered a crude approximation, and may not even be that if the minimum is highly non-quadratic.

If you have a constrained minimization problem, require a high-precision solution, and do not have a good initial guess, consider first feeding your constrained problem into FindGlobalMinimum(FuncIReadOnlyListDouble, Double, IReadOnlyListInterval, MultiExtremumSettings), which supports constraints but gives relatively lower precision solutions, then feeding the result of that method into this method, which finds relatively precise solutions but does not support constraints.

Reference