|  | GlobalCurveFitterFit(IListCurveFitDataSet, IListGlobalFitParameterInfo, Double, DoubleVector, DoubleVector) Method | 
            Performs the fit with parameter upper and lower bound constraints to the given datasets.
            The fitted function must be defined (real-valued) for all x.
            
Namespace: CenterSpace.NMath.CoreAssembly: NMath (in NMath.dll) Version: 7.4
 Syntax
Syntaxpublic double[][] Fit(
	IList<CurveFitDataSet> dataSets,
	IList<GlobalFitParameterInfo> parameterInfo,
	double[][] initialParameters,
	DoubleVector parameterLowerBounds,
	DoubleVector parameterUpperBounds
)
Public Function Fit ( 
	dataSets As IList(Of CurveFitDataSet),
	parameterInfo As IList(Of GlobalFitParameterInfo),
	initialParameters As Double()(),
	parameterLowerBounds As DoubleVector,
	parameterUpperBounds As DoubleVector
) As Double()()
public:
array<array<double>^>^ Fit(
	IList<CurveFitDataSet^>^ dataSets, 
	IList<GlobalFitParameterInfo^>^ parameterInfo, 
	array<array<double>^>^ initialParameters, 
	DoubleVector^ parameterLowerBounds, 
	DoubleVector^ parameterUpperBounds
)
member Fit : 
        dataSets : IList<CurveFitDataSet> * 
        parameterInfo : IList<GlobalFitParameterInfo> * 
        initialParameters : float[][] * 
        parameterLowerBounds : DoubleVector * 
        parameterUpperBounds : DoubleVector -> float[][] Parameters
- dataSets  IListCurveFitDataSet
- >Datasets to fit.
- parameterInfo  IListGlobalFitParameterInfo
- Parameter information.
- initialParameters  Double
- Initial parameter values. initialParameters[i][j] is 
            the initial value of the ith parameter for the jth data set.
- parameterLowerBounds  DoubleVector
- Parameter lower bounds. One for each parameter in
            the parameterized function geing fit.
- parameterUpperBounds  DoubleVector
- Parameter upper bounds. One for each parameter in
            the parameterized function geing fit.
Return Value
Double
            Parameter estimates as a jagged array of doubles. 
            Note that we will get one parameter estimate for each shared
            parameter and N parameter estimates for each non-shared parameter,
            where N is the number of data sets.
            For example, p[i][j] is the value of the
            ith parameter for the jth data set. If the ith parameter is shared
            only the index j = 0 will be valid since we have only one parameter
            value. If the ith parameter is shared between the N data sets then
            indices j = 0, 1,..., N-1 are valid. For example:
            p[i][0] - value for the ith parameter if shared.
            p[i][0], p[i][1],..., p[i][N-1] - values for the ith non-shared 
            parameter for data sets 0, 1,..., N-1.
            
            Parameter estimates satisfy
            
parameterLowerBound[i]  < p[i][j] >  parameterUpperBounds[i]
            for each data set j.
            
 See Also
See Also