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MultipleCurveFitFunction Class

Function for simulatenous fitting of multiple data sets with shared fitting parameters. MultipleCurveFit
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreParameterizedMultivariableFunction
    CenterSpace.NMath.CoreMultipleCurveFitFunction

Namespace: CenterSpace.NMath.Core
Assembly: NMath (in NMath.dll) Version: 7.4
Syntax
[SerializableAttribute]
public class MultipleCurveFitFunction : ParameterizedMultivariableFunction, 
	ICloneable

The MultipleCurveFitFunction type exposes the following members.

Constructors
 NameDescription
Public methodMultipleCurveFitFunction(Int32, IListMultipleFitCurveInfo) Creates a MultipleCurveFitFunction instance with the specied number of parametrs for the given data sets. A default value of 1e-8 for the central difference delta is the used in the central difference algorithm for computing Jacobians.
Public methodMultipleCurveFitFunction(Int32, IListMultipleFitCurveInfo, Double) Creates a MultipleCurveFitFunction instance with the specied number of parameters and central difference delta for the given data sets. The central difference delta is the used in the central difference algorithm for computing Jacobians
Public methodMultipleCurveFitFunction(Int32, IListInt32, IListFuncDoubleVector, Double, Double) Creates a MultipleCurveFitFunction instance with the specied number of parameters and central difference delta for the given data sets with the given numbers of points. A default value of 1e-8 for the central difference delta is the used in the central difference algorithm for computing Jacobians
Public methodMultipleCurveFitFunction(Int32, IListInt32, IListFuncDoubleVector, Double, Double, Double) Creates a MultipleCurveFitFunction instance with the specied number of parameters and central difference delta for the given data sets with the given numbers of points. The central difference delta is the used in the central difference algorithm for computing Jacobians
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Properties
 NameDescription
Public propertyCentralDifferenceDelta The delta used in the central difference algorithm for computing the Jacobian with respect to the parameters
(Inherited from ParameterizedMultivariableFunction)
Public propertyNumberOfDataSets Gets the number of data sets.
Public propertyNumberOfParameters Gets and sets the number of parameters.
(Inherited from ParameterizedMultivariableFunction)
Public propertyNumPointsPerCurve Gets a list containing the number of data points for each data set.
Public propertyParameterizedFunctions Gets the list of parameterized functions. The ith parameterized function corresponds to the ith data set.
Public propertyXdimension Gets and sets the dimension of the function domain. Vector arguments to the function must have length equal to this value.
(Inherited from ParameterizedMultivariableFunction)
Public propertyYDimension Gets and sets the dimension of the function range. Vectors returned by this function will have this length.
(Inherited from ParameterizedMultivariableFunction)
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Methods
 NameDescription
Public methodClone Returns a deep copy of the base. Deriving classes must override this method.
(Inherited from ParameterizedMultivariableFunction)
Public methodEvaluate(Double, Double) Evaluates the function for the given set of parameters at the given point.
(Inherited from ParameterizedMultivariableFunction)
Public methodEvaluate(DoubleVector, DoubleVector, DoubleVector) Evaluates the function for the given set of parameters at the given point.
(Overrides ParameterizedMultivariableFunctionEvaluate(DoubleVector, DoubleVector, DoubleVector))
Public methodJacobianWithRespectToParameters(Double, Double, DoubleMatrix) Method for calculating the Jacobian with respect to the parameters while keeping x fixed at the specified value.
(Inherited from ParameterizedMultivariableFunction)
Public methodJacobianWithRespectToParameters(DoubleVector, DoubleVector, DoubleMatrix) Method for calculating the Jacobian with respect to the parameters while keeping x fixed at the specified value.
(Inherited from ParameterizedMultivariableFunction)
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See Also