|  | DownhillSimplexMinimizerMinimize(MultiVariableFunction, DoubleVector) Method | 
Note: This API is now obsolete.
            Minimizes the given function near the given starting point.
            
Namespace: CenterSpace.NMath.CoreAssembly: NMath (in NMath.dll) Version: 7.4
 Syntax
Syntax[ObsoleteAttribute("This method is obsolete. Call method Minimize( DoubleFunctional f, DoubleVector x ).")]
public DoubleVector Minimize(
	MultiVariableFunction f,
	DoubleVector x
)<ObsoleteAttribute("This method is obsolete. Call method Minimize( DoubleFunctional f, DoubleVector x ).")>
Public Function Minimize ( 
	f As MultiVariableFunction,
	x As DoubleVector
) As DoubleVectorpublic:
[ObsoleteAttribute(L"This method is obsolete. Call method Minimize( DoubleFunctional f, DoubleVector x ).")]
virtual DoubleVector^ Minimize(
	MultiVariableFunction^ f, 
	DoubleVector^ x
) sealed
[<ObsoleteAttribute("This method is obsolete. Call method Minimize( DoubleFunctional f, DoubleVector x ).")>]
abstract Minimize : 
        f : MultiVariableFunction * 
        x : DoubleVector -> DoubleVector 
[<ObsoleteAttribute("This method is obsolete. Call method Minimize( DoubleFunctional f, DoubleVector x ).")>]
override Minimize : 
        f : MultiVariableFunction * 
        x : DoubleVector -> DoubleVector Parameters
- f  MultiVariableFunction
- The function to minimize.
- x  DoubleVector
- The starting point.
Return Value
DoubleVector
            The local minimum of 
function near 
x.
            
Implements
IMultiVariableMinimizerMinimize(MultiVariableFunction, DoubleVector) Remarks
Remarks
            A starting simplex is constructed from the given point by adding 
1.0
            in each dimension. For example, in two dimensions the simplex is a
            triangle:
            
( x0, x1 )
( x0 + 1, x1 )
( x0, x1 + 1 )
            Iteration stops when either the decrease in function value is less 
            than the tolerance, or the maximum number of iterations is reached.
            Setting the error tolerance to less than zero ensures that the maximum number
            of iterations is always reached.
            
 See Also
See Also