public void BaselineHazardTest()
{
double[,] data =
{
// t c in
{ 8, 0, -1.2372626521865966 },
{ 4, 1, 0.22623087329625477 },
{ 12, 0, -0.8288458543774289 },
{ 6, 0, 0.49850873850236665 },
{ 10, 0, -0.38639432341749696 },
{ 8, 1, 1.0430644689145904 },
{ 5, 0, -1.6797141831465285 },
{ 5, 0, 1.0770992020653544 },
{ 3, 1, 1.0770992020653544 },
{ 14, 1, -0.38639432341749696 },
{ 8, 0, -0.8969153206789568 },
{ 11, 0, 1.6897243987791061 },
{ 7, 0, -1.2712973853373605 },
{ 7, 0, -0.38639432341749696 },
{ 7, 1, -0.45446378971902495 },
{ 12, 0, 0.4644740053516027 },
{ 8, 0, 1.4514812667237584 },
};
double[] time = data.GetColumn(0);
SurvivalOutcome[] censor = data.GetColumn(1).To <SurvivalOutcome[]>();
double[][] inputs = data.GetColumn(2).ToJagged();
var regression = new ProportionalHazards(1);
var target = new ProportionalHazardsNewtonRaphson(regression);
target.Normalize = false;
target.Lambda = 0;
regression.Coefficients[0] = 0.47983261821350764;
double error = target.Run(inputs, time, censor);
/* Tested against http://statpages.org/prophaz2.html
* 13, 8, 0
* 56, 4, 1
* 25, 12, 0
* 64, 6, 0
* 38, 10, 0
* 80, 8, 1
* 0 , 5, 0
* 81, 5, 0
* 81, 3, 1
* 38, 14, 1
* 23, 8, 0
* 99, 11, 0
* 12, 7, 0
* 38, 7, 0
* 36, 7, 1
* 63, 12, 0
* 92, 8, 0
*/
double[] baseline =
{
regression.Survival(3), // 0.9465
regression.Survival(4), // 0.8919
regression.Survival(7), // 0.8231
regression.Survival(8), // 0.7436
regression.Survival(12), // 0.7436
regression.Survival(14), // 0.0000
};
Assert.AreEqual(0.9465, baseline[0], 1e-4);
Assert.AreEqual(0.8919, baseline[1], 1e-4);
Assert.AreEqual(0.8231, baseline[2], 1e-4);
Assert.AreEqual(0.7436, baseline[3], 1e-4);
Assert.AreEqual(0.7436, baseline[4], 1e-4);
Assert.AreEqual(0.0000, baseline[5], 1e-4);
// The value of the baseline must be exact the same if it was computed
// after the Newton-Raphson or in a standalone EmpiricalHazard computation
double[] outputs = inputs.Apply(x => regression.Compute(x));
var empirical = EmpiricalHazardDistribution.Estimate(time, censor, outputs);
baseline = new[]
{
empirical.ComplementaryDistributionFunction(3), // 0.9465
empirical.ComplementaryDistributionFunction(4), // 0.8919
empirical.ComplementaryDistributionFunction(7), // 0.8231
empirical.ComplementaryDistributionFunction(8), // 0.7436
empirical.ComplementaryDistributionFunction(12), // 0.7436
empirical.ComplementaryDistributionFunction(14), // 0.0000
};
Assert.AreEqual(0.9465, baseline[0], 1e-4);
Assert.AreEqual(0.8919, baseline[1], 1e-4);
Assert.AreEqual(0.8231, baseline[2], 1e-4);
Assert.AreEqual(0.7436, baseline[3], 1e-4);
Assert.AreEqual(0.7436, baseline[4], 1e-4);
Assert.AreEqual(0.0000, baseline[5], 1e-4);
}
public void PredictTest1()
{
// Data from: http://statpages.org/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 },
};
var regression = new ProportionalHazards(1);
double[][] inputs = data.GetColumn(0).ToJagged();
double[] time = data.GetColumn(1);
int[] censor = data.GetColumn(2).ToInt32();
var target = new ProportionalHazardsNewtonRaphson(regression);
double error = target.Run(inputs, time, censor);
// Tested against http://statpages.org/prophaz2.html
Assert.AreEqual(0.3770, regression.Coefficients[0], 1e-4);
Assert.AreEqual(0.2542, regression.StandardErrors[0], 1e-4);
Assert.AreEqual(51.18181818181818, regression.Offsets[0]);
double mean = regression.Offsets[0];
// Baseline survivor function at predictor means
double[] baseline =
{
regression.Survival(2),
regression.Survival(7),
regression.Survival(9),
regression.Survival(10),
};
// Tested against http://statpages.org/prophaz2.html
Assert.AreEqual(0.9979, baseline[0], 1e-4);
Assert.AreEqual(0.9820, baseline[1], 1e-4);
Assert.AreEqual(0.9525, baseline[2], 1e-4);
Assert.AreEqual(0.8310, baseline[3], 1e-4);
double[] expected =
{
0, 2.51908236823927, 0.000203028311170645, 4.67823782106946E-06, 1.07100164957025,
0.118590728553659, 0.000203028311170645, 0.0187294821517496, 1.31028937819308E-05,
0.436716853556834, 5.14665484304978
};
double[] actual = new double[inputs.Length];
for (int i = 0; i < inputs.Length; i++)
{
double a = actual[i] = regression.Compute(inputs[i], time[i]);
double e = expected[i];
Assert.AreEqual(e, a, 1e-3);
}
// string exStr = actual.ToString(CSharpArrayFormatProvider.InvariantCulture);
}
