public void MultivariateLinearRegressionAgreement()
{
Random rng = new Random(1);
MultivariateSample SA = new MultivariateSample(2);
for (int i = 0; i < 10; i++) {
SA.Add(rng.NextDouble(), rng.NextDouble());
}
FitResult RA = SA.LinearRegression(0);
ColumnVector PA = RA.Parameters;
SymmetricMatrix CA = RA.CovarianceMatrix;
MultivariateSample SB = SA.Columns(1, 0);
FitResult RB = SB.LinearRegression(1);
ColumnVector PB = RB.Parameters;
SymmetricMatrix CB = RB.CovarianceMatrix;
Assert.IsTrue(TestUtilities.IsNearlyEqual(PA[0], PB[1])); Assert.IsTrue(TestUtilities.IsNearlyEqual(PA[1], PB[0]));
Assert.IsTrue(TestUtilities.IsNearlyEqual(CA[0, 0], CB[1, 1])); Assert.IsTrue(TestUtilities.IsNearlyEqual(CA[0, 1], CB[1, 0])); Assert.IsTrue(TestUtilities.IsNearlyEqual(CA[1, 1], CB[0, 0]));
Assert.IsTrue(TestUtilities.IsNearlyEqual(RA.GoodnessOfFit.Statistic, RB.GoodnessOfFit.Statistic));
BivariateSample SC = SA.TwoColumns(1, 0);
FitResult RC = SC.LinearRegression();
ColumnVector PC = RC.Parameters;
SymmetricMatrix CC = RC.CovarianceMatrix;
Assert.IsTrue(TestUtilities.IsNearlyEqual(PA, PC));
Assert.IsTrue(TestUtilities.IsNearlyEqual(CA, CC));
Assert.IsTrue(TestUtilities.IsNearlyEqual(RA.GoodnessOfFit.Statistic, RC.GoodnessOfFit.Statistic));
}