| Member Functions | |||
| confidenceInterval() operator=() |
standardError() value() |
waldChiSqStatCriticalValue() waldChiSqStatistic() |
waldChiSqStatPvalue() |
#include <rw/analytics/logregress.h> #include <rw/analytics/logparam.h> RWLogisticRegression lr; RWTValVector<RWLogisticRegressionParam> p = lr.parameterEstimates();
RWLogisticRegressionParam is the container class for logistic regression parameter estimates and their associated statistical quantities. The estimates are described in Section 3.2.4.
#include <rw/analytics/logregress.h>
#include <rw/rstream.h>
int main()
{
RWGenMat<double> predData = "5x2
[1 234 2 431 3 333 4 654 5 788]";
RWMathVec<RWBoolean> obsData(5, rwUninitialized );
obsData[0] = obsData[3] = obsData[4] = TRUE;
obsData[1] = obsData[2] = FALSE;
RWLogisticRegression lr( predData, obsData );
// Make sure parameter calculation succeeded.
if ( lr.fail() )
{
return 0;
}
double sigLevel = .05;
// Print out model parameter estimate info.
RWTValVector<RWLogisticRegressionParam> params =
lr.parameterEstimates();
for ( size_t i = 0; i < params.length(); i++ )
{
cout << "Model parameter " << i <<
(i==0UL?" Intercept:":":") << endl;
cout << " value: " <<
params[i].value() << endl;
cout << " standard error: " <<
params[i].standardError() << endl;
cout << " Wald statistic: " <<
params[i].waldChiSqStatistic() << endl;
cout << " Wald statistic P-value: " <<
params[i].waldChiSqStatPValue() << endl;
cout << " Wald statistic critical value: "
<< params[i].waldChiSqStatCriticalValue(sigLevel)
<< endl;
cout << " " << sigLevel << " confidence interval: " << "["
<< params[i].confidenceInterval(sigLevel).lowerBound()
<< ", "
<< params[i].confidenceInterval(sigLevel).upperBound()
<< "]\n" << endl;
}
return 0;
}
RWLogisticRegressionParam();
Constructs an empty fitted parameter object. Behavior undefined.
RWLogisticRegressionParam(const RWLogisticRegressionParam& a);
Constructs a copy of a.
RWInterval<double> confidenceInterval(double alpha) const;
Returns an alpha level confidence interval for the parameter.
double standardError() const;
Returns the estimated standard error for the fitted value. This is the square root of the estimated variance, V, described in Section 3.3.2.
double waldChiSqStatCriticalValue(double alpha) const;
Returns the critical value for the Wald chi-square statistic at significance level alpha.
double waldChiSqStatistic() const;
Returns the Wald chi-square statistic for the hypothesis that the parameter is equal to 0.
double waldChiSqStatPvalue() const;
Returns the P-value for the parameter Wald chi-square statistic.
double value() const;
Returns the least squares estimate for the parameter.
RWLogisticRegressionParam& operator=(const RWLogisticRegressionParam&);
Assignment operator.
©Copyright 1999, Rogue Wave Software, Inc.
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