Accord.Tests.Statistics.NewtonRaphsonCoxLearningTest.PredictTest1 C# (CSharp) Method

        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);
        }