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GoodnessOfFit Class

Class GoodnessOfFit tests goodness of fit for least squares model-fitting classes, such as LinearRegression, PolynomialLeastSquares, and OneVariableFunctionFitter.
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreGoodnessOfFit

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.3
Syntax
[SerializableAttribute]
public class GoodnessOfFit : ICloneable

The GoodnessOfFit type exposes the following members.

Constructors
Properties
  NameDescription
Public propertyAdjustedRsquared
Gets the adjusted coefficient of determination.
Public propertyErrorDegreesOfFreedom
Gets the number of degrees of freedom for the model error.
Public propertyFStatistic
Gets the overall F-statistic for the model.
Public propertyFStatisticPValue
Gets the p-value for the F-statistic.
Public propertyMeanSquaredRegression
Gets the mean squared for the regression.
Public propertyMeanSquaredResidual
Gets the mean squared residual.
Public propertyModelDegreesOfFreedom
Gets the number of degrees of freedom for the model.
Public propertyParameters
Gets an array of parameter objects which may be used to perform hypothesis tests on individual parameters in the model.
Public propertyRegressionSumOfSquares
Gets the regression sum of squares.
Public propertyResidualStandardError
Gets the residual standard error.
Public propertyResidualSumOfSquares
Gets the residual sum of squares.
Public propertyRSquared
Gets the coefficient of determination.
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Methods
  NameDescription
Public methodClone
Creates a deep copy of this GoodnessOfFit.
Public methodFStatisticCriticalValue
Computes the critical value for the F-statistic at the given signicance level.
Public methodStatic memberGetGoodnessOfFitM
Constructs a GoodnessOfFit instance from the given OneVariableFunctionFitter.
Public methodToString
String representation of a GoodnessOfFit object.
(Overrides ObjectToString.)
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Remarks
Available statistics include the residual standard error, the coefficient of determination (R2 and "adjusted" R2), the F-statistic for the overall model with its numerator and denominator degrees of freedom, and standard errors, t-statistics, and corresponding (two-sided) p-values for the model parameters.
See Also