public void ConstructorTest()
        {
            // Create a Geometric distribution with 42% success probability
            var dist = new GeometricDistribution(probabilityOfSuccess: 0.42);

            double mean = dist.Mean;     // 1.3809523809523812
            double median = dist.Median; // 1
            double var = dist.Variance;  // 3.2879818594104315
            double mode = dist.Mode;     // 0

            double cdf = dist.DistributionFunction(k: 2);               // 0.80488799999999994
            double ccdf = dist.ComplementaryDistributionFunction(k: 2); // 0.19511200000000006

            double pdf1 = dist.ProbabilityMassFunction(k: 0); // 0.42
            double pdf2 = dist.ProbabilityMassFunction(k: 1); // 0.2436
            double pdf3 = dist.ProbabilityMassFunction(k: 2); // 0.141288

            double lpdf = dist.LogProbabilityMassFunction(k: 2); // -1.956954918588067

            int icdf1 = dist.InverseDistributionFunction(p: 0.17); // 0
            int icdf2 = dist.InverseDistributionFunction(p: 0.46); // 1
            int icdf3 = dist.InverseDistributionFunction(p: 0.87); // 3

            double hf = dist.HazardFunction(x: 0); // 0.72413793103448265
            double chf = dist.CumulativeHazardFunction(x: 0); // 0.54472717544167193

            string str = dist.ToString(CultureInfo.InvariantCulture); // "Geometric(x; p = 0.42)"

            Assert.AreEqual(1.3809523809523812, mean);
            Assert.AreEqual(1, median);
            Assert.AreEqual(0, mode);
            Assert.AreEqual(3.2879818594104315, var);
            Assert.AreEqual(0.54472717544167193, chf, 1e-10);
            Assert.AreEqual(0.80488799999999994, cdf);
            Assert.AreEqual(0.42, pdf1);
            Assert.AreEqual(0.2436, pdf2);
            Assert.AreEqual(0.14128800000000002, pdf3);
            Assert.AreEqual(-1.956954918588067, lpdf);
            Assert.AreEqual(0.72413793103448265, hf);
            Assert.AreEqual(0.19511200000000006, ccdf);
            Assert.AreEqual(0, icdf1);
            Assert.AreEqual(1, icdf2);
            Assert.AreEqual(3, icdf3);
            Assert.AreEqual("Geometric(x; p = 0.42)", str);

            var range1 = dist.GetRange(0.95);
            var range2 = dist.GetRange(0.99);
            var range3 = dist.GetRange(0.01);

            Assert.AreEqual(0, range1.Min);
            Assert.AreEqual(5, range1.Max);
            Assert.AreEqual(0, range2.Min);
            Assert.AreEqual(8, range2.Max);
            Assert.AreEqual(0, range3.Min);
            Assert.AreEqual(8, range3.Max);
        }
Example #2
0
        public void ConstructorTest()
        {
            // Create a Geometric distribution with 42% success probability
            var dist = new GeometricDistribution(probabilityOfSuccess: 0.42);

            double mean   = dist.Mean;                                  // 1.3809523809523812
            double median = dist.Median;                                // 1
            double var    = dist.Variance;                              // 3.2879818594104315
            double mode   = dist.Mode;                                  // 0

            double cdf  = dist.DistributionFunction(k: 2);              // 0.80488799999999994
            double ccdf = dist.ComplementaryDistributionFunction(k: 2); // 0.19511200000000006

            double pdf1 = dist.ProbabilityMassFunction(k: 0);           // 0.42
            double pdf2 = dist.ProbabilityMassFunction(k: 1);           // 0.2436
            double pdf3 = dist.ProbabilityMassFunction(k: 2);           // 0.141288

            double lpdf = dist.LogProbabilityMassFunction(k: 2);        // -1.956954918588067

            int icdf1 = dist.InverseDistributionFunction(p: 0.17);      // 0
            int icdf2 = dist.InverseDistributionFunction(p: 0.46);      // 1
            int icdf3 = dist.InverseDistributionFunction(p: 0.87);      // 3

            double hf  = dist.HazardFunction(x: 0);                     // 0.72413793103448265
            double chf = dist.CumulativeHazardFunction(x: 0);           // 0.54472717544167193

            string str = dist.ToString(CultureInfo.InvariantCulture);   // "Geometric(x; p = 0.42)"

            Assert.AreEqual(1.3809523809523812, mean);
            Assert.AreEqual(1, median);
            Assert.AreEqual(0, mode);
            Assert.AreEqual(3.2879818594104315, var);
            Assert.AreEqual(0.54472717544167193, chf, 1e-10);
            Assert.AreEqual(0.80488799999999994, cdf);
            Assert.AreEqual(0.42, pdf1);
            Assert.AreEqual(0.2436, pdf2);
            Assert.AreEqual(0.14128800000000002, pdf3);
            Assert.AreEqual(-1.956954918588067, lpdf);
            Assert.AreEqual(0.72413793103448265, hf);
            Assert.AreEqual(0.19511200000000006, ccdf);
            Assert.AreEqual(0, icdf1);
            Assert.AreEqual(1, icdf2);
            Assert.AreEqual(3, icdf3);
            Assert.AreEqual("Geometric(x; p = 0.42)", str);

            var range1 = dist.GetRange(0.95);
            var range2 = dist.GetRange(0.99);
            var range3 = dist.GetRange(0.01);

            Assert.AreEqual(0, range1.Min);
            Assert.AreEqual(5, range1.Max);
            Assert.AreEqual(0, range2.Min);
            Assert.AreEqual(8, range2.Max);
            Assert.AreEqual(0, range3.Min);
            Assert.AreEqual(8, range3.Max);
        }
Example #3
0
        public void ProbabilityMassFunctionTest()
        {
            double successProbability    = 0.42;
            GeometricDistribution target = new GeometricDistribution(successProbability);

            double[] expected = { 0, 0.42, 0.2436, 0.141288, 0.08194704, 0.0475292832, 0.027566984256 };

            for (int i = 0; i < expected.Length; i++)
            {
                double actual = target.ProbabilityMassFunction(i - 1);
                Assert.AreEqual(expected[i], actual, 1e-10);
                Assert.IsFalse(Double.IsNaN(actual));
            }
        }
        public void ProbabilityMassFunctionTest()
        {
            double successProbability = 0.42;
            GeometricDistribution target = new GeometricDistribution(successProbability);

            double[] expected = { 0, 0.42, 0.2436, 0.141288, 0.08194704, 0.0475292832, 0.027566984256 };

            for (int i = 0; i < expected.Length; i++)
            {
                double actual = target.ProbabilityMassFunction(i - 1);
                Assert.AreEqual(expected[i], actual, 1e-10);
                Assert.IsFalse(Double.IsNaN(actual));
            }
        }