private void computeInformation()
{
// Store model information
this.result = regression.Compute(inputData, timeData);
this.deviance = regression.GetDeviance(inputData, timeData, censorData);
this.logLikelihood = regression.GetPartialLogLikelihood(inputData, timeData, censorData);
this.chiSquare = regression.ChiSquare(inputData, timeData, censorData);
// Store coefficient information
for (int i = 0; i < regression.Coefficients.Length; i++)
{
this.standardErrors[i] = regression.StandardErrors[i];
this.waldTests[i] = regression.GetWaldTest(i);
this.coefficients[i] = regression.Coefficients[i];
this.confidences[i] = regression.GetConfidenceInterval(i);
this.hazardRatios[i] = regression.GetHazardRatio(i);
}
}
public void RunTest()
{
// Data from: http://www.sph.emory.edu/~cdckms/CoxPH/prophaz2.html
double[,] data =
{
{ 50, 1, 0 },
{ 70, 2, 1 },
{ 45, 3, 0 },
{ 35, 5, 0 },
{ 62, 7, 1 },
{ 50, 11, 0 },
{ 45, 4, 0 },
{ 57, 6, 0 },
{ 32, 8, 0 },
{ 57, 9, 1 },
{ 60, 10, 1 },
};
ProportionalHazards regression = new ProportionalHazards(1);
regression.Coefficients[0] = 0.37704239281494084;
regression.StandardErrors[0] = 0.25415755113043753;
double[][] inputs = data.GetColumn(0).ToJagged();
double[] time = data.GetColumn(1);
SurvivalOutcome[] output = data.GetColumn(2).To <SurvivalOutcome[]>();
{
double actual = -2 * regression.GetPartialLogLikelihood(inputs, time, output);
double expected = 4.0505;
Assert.AreEqual(expected, actual, 1e-4);
Assert.IsFalse(Double.IsNaN(actual));
}
{
var test = regression.GetWaldTest(0);
Assert.AreEqual(0.1379, test.PValue, 1e-4);
}
{
var ci = regression.GetConfidenceInterval(0);
Assert.AreEqual(0.8859, ci.Min, 1e-4);
Assert.AreEqual(2.3993, ci.Max, 1e-4);
}
{
double actual = regression.GetHazardRatio(0);
double expected = 1.4580;
Assert.AreEqual(expected, actual, 1e-4);
}
{
var chi = regression.ChiSquare(inputs, time, output);
Assert.AreEqual(7.3570, chi.Statistic, 1e-4);
Assert.AreEqual(1, chi.DegreesOfFreedom);
Assert.AreEqual(0.0067, chi.PValue, 1e-3);
}
}
