RWLinearRegressionFTest

Does not inherit

• Local Index
• Synopsis
• Description
• Example
• Public Constructors
• Public Member Functions
• Public Member Operator

Members

criticalValue() FStatisticPValue()

FStatisticValue() operator=()

reject() RWLinearRegressionFTest()

setHypothesis() setLinearRegression()

#include <rw/math/genmat.h>
#include <rw/math/mathvec.h>
#include <rw/analytics/linregress.h>
#include <rw/analytics/lrftest.h>

RWGenMat<double> predictorMatrix;
RWMathVec<double> observationVector;
RWLinearRegression lr(predictorMatrix, observationVector);
RWLinearRegressionFTest ftest(lr);

Class RWLinearRegressionFTest can be used to test that the estimated parameters in a linear regression model are equal to a hypothesized vector of values. For example, it can test the hypothesis that all parameters are equal to 0. To be completely precise, the class tests the hypothesis that the estimated parameters are the solution to some specified system of linear equations. The test is based on the F statistic described in Section 3.2, "Multiple Linear Regression," in the Business Analysis Module User's Guide.

The following example creates a linear regression object and tests the hypothesis that all parameters are equal to 0 at a confidence level of 99 percent.

#include <rw/analytics/linregress.h>
#include <lrftest.h>

int main() {
 RWGenMat<double> predictorMatrix = 
                       "5x2 [1.2 2.1 8 7 3 3.2 6.4 4.6 2 2.3]";
 RWMathVec<double> observationVector = "[2.5 3.7 1.4 2.3 5.6]";

 RWLinearRegression lr(predictorMatrix, observationVector);
 RWLinearRegressionFTest FTest(lr);

 cout << "  f statistic value:   " << FTest.FStatisticValue() 
      << endl;
 cout << "  f statistic P-value: " << FTest.FStatisticPValue()
      << endl;
 cout << "  99% Critical value:  " << FTest.criticalValue(0.01)
      << endl;
 if ( FTest.reject(0.01) )
 {
   cout << "Reject H0 at significance level 0.01" << endl;
 }
 else
 {
   cout << "Fail to reject H0 at significance level 0.01" 
        << endl;

 }
 return 0;
}

RWLinearRegressionFTest();

Constructs an empty F test object. Behavior is undefined.

RWLinearRegressionFTest(const RWLinearRegressionFTest<T>& t);

Constructs a copy of t.

RWLinearRegressionFTest(const RWLinearRegression<T>& lr);

Constructs an F test for the hypothesis that .

RWLinearRegressionFTest(const RWLinearRegression& lr,
                        const RWGenMat<double>& A, 
                        const RWMathVec<double>& c);

Constructs an F test for the hypothesis that .

double 
criticalValue(double alpha) const;

Returns the critical value for the test at the significance level alpha.

double
FStatisticPValue() const;

Returns the P-value for the test.

double 
FStatisticValue() const;

Returns the value of the F statistic.

bool 
reject(double alpha=.05);

Returns true if the hypothesis being tested will be rejected at the significance level alpha.

void 
setHypothesis(const RWGenMat<double>& A,
              const RWMathVec<double>& c);

Sets the hypothesis being tested to .

void 
setLinearRegression(const RWLinearRegression& lr);

Sets the linear regression for which the hypothesis will be tested.

RWLinearRegressionFTest& 
operator=(const RWLinearRegressionFTest& ft);

Copies the contents of ft to self.

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