Class RWLogisticFitAnalysis

Class RWLogisticFitAnalysis is similar to class RWLinearRegression, which was described above. To use RWLogisticFitAnalysis, you specify a logistic regression, either at construction time or via the setLogisticRegression() member function, and query the object for the various fit analysis quantities. The following example demonstrates the procedure.

RWLogisticRegression model;

RWLogisticFitAnalysis logfit(model);

cout << "Pearson statistic: " << logfit.PearsonStatistic() << endl;

cout << "Pearson statistic p-value: " <<

logfit.PearsonStatisticPValue() << endl;

cout << "Pearson statistic 10% critical value: " <<

logfit.PearsonStatisticCriticalValue(0.10) << endl;

cout << "Pearson statistic degrees of freedom: " <<

logfit.PearsonStatisticDegreesOfFreedom() << endl;

cout << "Predictor data groups for Pearson statistic: " <<

logfit.predictorDataGroups() << endl;

cout << endl;

cout << "HL statistic: " << logfit.HLStatistic() << endl;

cout << "HL statistic p-value: " << logfit.HLStatisticPValue() <<

endl;

cout << "HL statistic 10% critical value: " <<

logfit.HLStatisticCriticalValue(0.10) << endl;

cout << "HL statistic degrees of freedom: " <<

logfit.HLStatisticDegreesOfFreedom() << endl;

cout << "Bin counts for predictions: " <<

logfit.HLStatisticOutputHistogram() << endl;

cout << "Bin counts for predictions associated \n

with positive observations: "

<< logfit.HLStatisticPosObsHistogram() << endl;

cout << endl;