Class MultiVariableFunctionFitter fits a generalized multivariable function to a set of points.

Namespace:  CenterSpace.NMath.Analysis
Assembly:  NMath (in NMath.dll) Version: 5.1.0.0

Syntax

C#
[SerializableAttribute]
[ObsoleteAttribute("Replaced by generic class MultiVariableFunctionFitter<M> : where M : INonlinearLeastSqMinimizer")]
public class MultiVariableFunctionFitter : ICloneable
Visual Basic (Declaration)
<SerializableAttribute> _
<ObsoleteAttribute("Replaced by generic class MultiVariableFunctionFitter<M> : where M : INonlinearLeastSqMinimizer")> _
Public Class MultiVariableFunctionFitter _
	Implements ICloneable
Visual C++
[SerializableAttribute]
[ObsoleteAttribute(L"Replaced by generic class MultiVariableFunctionFitter<M> : where M : INonlinearLeastSqMinimizer")]
public ref class MultiVariableFunctionFitter : ICloneable

Remarks

In the space of the function parameters, begining at a specified starting point, finds a minimum (possibly local) in the sum of the squared residuals with respect to a set of data points. You must supply at least as many data points to fit as your function has parameters.
For example, the following code fits a function of the form data to the following function: 
            F(p, x) = p[0]x[0]x[1]^2 + p[1]sin(x[0]) + p[2]x[1]^3;
to a set of 10 data points, beginning at point (10, 10, 10) in the parameter space.
CopyC#
DoubleMatrix x = new DoubleMatrix(10, 2);
x[Slice.All, 0] = new DoubleVector("3.6 7.7 9.3 4.1 8.6 2.8 1.3 7.9 10.0 5.4");
x[Slice.All, 1] = new DoubleVector("16.5 150.6 263.1 24.7 208.5 9.9 2.7 163.9 325.0 54.3");

DoubleVector yValues = new DoubleVector("95.09 23.11 60.63 48.59 89.12 76.97 45.68 1.84 82.17 44.47");
DoubleVector initial_parameters = new DoubleVector("10 10 10");

NMathFunctions.GeneralizedDoubleVectorDoubleFunction f = delegate(DoubleVector p, DoubleVector xdata)
{
  return Math.Pow(p[0] * xdata[0] * xdata[1], 2.0) + p[1] * Math.Sin(xdata[0]) + Math.Pow(p[2] * xdata[1], 3.0);
};

MultiVariableFunctionFitter fitter = new MultiVariableFunctionFitter(f);
DoubleVector solution = fitter.Fit(x, yValues, initial_parameters);
 Note that problems can have multiple local minima. Trying different initial parameter points is recommended for better solutions.

Inheritance Hierarchy

System..::.Object
  CenterSpace.NMath.Analysis..::.MultiVariableFunctionFitter

See Also