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); }