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LogisticRegressionFitAnalysisParameterCalc Class

Class for for calculating "goodness of fit" statistics for a logistic regression model.
Inheritance Hierarchy
SystemObject
  CenterSpace.NMath.CoreLogisticRegressionFitAnalysisParameterCalc

Namespace:  CenterSpace.NMath.Core
Assembly:  NMath (in NMath.dll) Version: 7.3
Syntax
[SerializableAttribute]
public class LogisticRegressionFitAnalysis<ParameterCalc> : ICloneable
where ParameterCalc : new(), ILogisticRegressionCalc

Type Parameters

ParameterCalc
The model parameter calculation class.

The LogisticRegressionFitAnalysisParameterCalc type exposes the following members.

Constructors
Properties
  NameDescription
Public propertyGStatistic
Gets the G statistic for the model. The G statistic is G = -2*ln[(likelihood without the variables)/(likelihood with the variables)]
Public propertyGStatisticPValue
Gets the p-value for the G statistic.
Public propertyLogLikelihood
Gets the log likelihood for the model.
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Methods
  NameDescription
Public methodClone
Creates a deep copy of self.
Public methodHLStatistic(Int32)
Gets the Hosmer Lemeshow statistic for the model using a specified number of groups. The default is 10 groups.
Public methodHLStatistic(FuncLogisticRegressionParameterCalc, Int32)
Computes the Hosmer Lemeshow statistic using the given functor to determine the number of groups and the number of observations in each group. The groups will be determined as follows: First, the observations are sorted in increasing order of their estimated probability. The first group will contain the first groups[0] observations from this sequence, the second group will contain the next groups[1] observations, and so forth.
Public methodHLStatistic(Int32, IEqualityComparerDoubleVector)
Calculates the Hosmer Lemeshow statistic for the model using the specified number of groups and the given comparer to determine equality of covariate patterns.
Public methodPearsonStatistic
Computes the Pearson chi-square statistic and related quantities from the Pearson residuals. To determine if two observations are the same (share the same covariate pattern) thier variable values are compared using a relative compare with a tolerance of 1e-6.
Public methodPearsonStatistic(IEqualityComparerDoubleVector)
Computes the Pearson chi-square statistic and related quantities from the Pearson residuals. To determine if two observations are the same (share the same covariate pattern) thier variable values are compared using the given comparer object.
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See Also