示例#1
0
        public void GammaDistributionConstructorTest2()
        {
            var gamma = new GammaDistribution(theta: 4, k: 2);

            double mean   = gamma.Mean;                                     // 8.0
            double median = gamma.Median;                                   // 6.7133878418421506
            double var    = gamma.Variance;                                 // 32.0

            double cdf  = gamma.DistributionFunction(x: 0.27);              // 0.002178158242390601
            double pdf  = gamma.ProbabilityDensityFunction(x: 0.27);        // 0.015773530285395465
            double lpdf = gamma.LogProbabilityDensityFunction(x: 0.27);     // -4.1494220422235433
            double ccdf = gamma.ComplementaryDistributionFunction(x: 0.27); // 0.99782184175760935
            double icdf = gamma.InverseDistributionFunction(p: cdf);        // 0.26999998689819171

            double hf  = gamma.HazardFunction(x: 0.27);                     // 0.015807962529274005
            double chf = gamma.CumulativeHazardFunction(x: 0.27);           // 0.0021805338793574793

            string str = gamma.ToString(CultureInfo.InvariantCulture);      // "Γ(x; k = 2, θ = 4)"

            Assert.AreEqual(8.0, mean);
            Assert.AreEqual(6.7133878418421506, median, 1e-6);
            Assert.AreEqual(32.0, var);
            Assert.AreEqual(0.0021805338793574793, chf);
            Assert.AreEqual(0.002178158242390601, cdf);
            Assert.AreEqual(0.015773530285395465, pdf);
            Assert.AreEqual(-4.1494220422235433, lpdf);
            Assert.AreEqual(0.015807962529274005, hf);
            Assert.AreEqual(0.99782184175760935, ccdf);
            Assert.AreEqual(0.26999998689819171, icdf, 1e-6);
            Assert.AreEqual("Γ(x; k = 2, θ = 4)", str);

            double p05 = gamma.DistributionFunction(median);

            Assert.AreEqual(0.5, p05, 1e-6);
        }
示例#2
0
        public void GammaDistributionConstructorTest2()
        {
            var gamma = new GammaDistribution(theta: 4, k: 2);

            double mean = gamma.Mean;     // 8.0
            double median = gamma.Median; // 6.7133878418421506
            double var = gamma.Variance;  // 32.0

            double cdf = gamma.DistributionFunction(x: 0.27); // 0.002178158242390601
            double pdf = gamma.ProbabilityDensityFunction(x: 0.27); // 0.015773530285395465
            double lpdf = gamma.LogProbabilityDensityFunction(x: 0.27); // -4.1494220422235433
            double ccdf = gamma.ComplementaryDistributionFunction(x: 0.27); // 0.99782184175760935
            double icdf = gamma.InverseDistributionFunction(p: cdf); // 0.26999998689819171

            double hf = gamma.HazardFunction(x: 0.27); // 0.015807962529274005
            double chf = gamma.CumulativeHazardFunction(x: 0.27); // 0.0021805338793574793

            string str = gamma.ToString(CultureInfo.InvariantCulture); // "Γ(x; k = 2, θ = 4)"

            Assert.AreEqual(8.0, mean);
            Assert.AreEqual(6.7133878418421506, median, 1e-6);
            Assert.AreEqual(32.0, var);
            Assert.AreEqual(0.0021805338793574793, chf);
            Assert.AreEqual(0.002178158242390601, cdf);
            Assert.AreEqual(0.015773530285395465, pdf);
            Assert.AreEqual(-4.1494220422235433, lpdf);
            Assert.AreEqual(0.015807962529274005, hf);
            Assert.AreEqual(0.99782184175760935, ccdf);
            Assert.AreEqual(0.26999998689819171, icdf, 1e-6);
            Assert.AreEqual("Γ(x; k = 2, θ = 4)", str);

            double p05 = gamma.DistributionFunction(median);
            Assert.AreEqual(0.5, p05, 1e-6);
        }
        public void MedianTest()
        {
            double shape = 0.4;
            double scale = 4.2;

            GammaDistribution target = new GammaDistribution(scale, shape);

            Assert.AreEqual(target.Median, target.InverseDistributionFunction(0.5));
        }
        public void GammaDistributionConstructorTest2()
        {
            #region doc_ctor
            // Create a Γ-distribution with k = 2 and θ = 4
            var gamma = new GammaDistribution(theta: 4, k: 2);

            // Common measures
            double mean   = gamma.Mean;     // 8.0
            double median = gamma.Median;   // 6.7133878418421506
            double var    = gamma.Variance; // 32.0
            double mode   = gamma.Mode;     // 4.0

            // Cumulative distribution functions
            double cdf  = gamma.DistributionFunction(x: 0.27);              // 0.002178158242390601
            double ccdf = gamma.ComplementaryDistributionFunction(x: 0.27); // 0.99782184175760935
            double icdf = gamma.InverseDistributionFunction(p: cdf);        // 0.26999998689819171

            // Probability density functions
            double pdf  = gamma.ProbabilityDensityFunction(x: 0.27);    // 0.015773530285395465
            double lpdf = gamma.LogProbabilityDensityFunction(x: 0.27); // -4.1494220422235433

            // Hazard (failure rate) functions
            double hf  = gamma.HazardFunction(x: 0.27);           // 0.015807962529274005
            double chf = gamma.CumulativeHazardFunction(x: 0.27); // 0.0021805338793574793

            // String representation
            string str = gamma.ToString(CultureInfo.InvariantCulture); // "Γ(x; k = 2, θ = 4)"
            #endregion

            Assert.AreEqual(8.0, mean);
            Assert.AreEqual(6.7133878418421506, median, 1e-6);
            Assert.AreEqual(32.0, var);
            Assert.AreEqual(4.0, mode);
            Assert.AreEqual(0.0021805338793574793, chf, 1e-10);
            Assert.AreEqual(0.002178158242390601, cdf, 1e-10);
            Assert.AreEqual(0.015773530285395465, pdf, 1e-10);
            Assert.AreEqual(-4.1494220422235433, lpdf, 1e-10);
            Assert.AreEqual(0.015807962529274005, hf, 1e-10);
            Assert.AreEqual(0.99782184175760935, ccdf, 1e-10);
            Assert.AreEqual(0.26999998689819171, icdf, 1e-6);
            Assert.AreEqual("Γ(x; k = 2, θ = 4)", str);

            double p05 = gamma.DistributionFunction(median);
            Assert.AreEqual(0.5, p05, 1e-6);

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

            Assert.AreEqual(1.4214460427946485, range1.Min, 1e-10);
            Assert.AreEqual(18.975458073562308, range1.Max, 1e-10);
            Assert.AreEqual(0.59421896101306348, range2.Min, 1e-10);
            Assert.AreEqual(26.553408271975243, range2.Max, 1e-10);
            Assert.AreEqual(0.59421896101306348, range3.Min, 1e-10);
            Assert.AreEqual(26.553408271975243, range3.Max, 1e-10);
        }
        public void GammaDistributionConstructorTest2()
        {
            var gamma = new GammaDistribution(theta: 4, k: 2);

            double mean = gamma.Mean;     // 8.0
            double median = gamma.Median; // 6.7133878418421506
            double var = gamma.Variance;  // 32.0
            double mode = gamma.Mode;     // 4.0

            double cdf = gamma.DistributionFunction(x: 0.27); // 0.002178158242390601
            double pdf = gamma.ProbabilityDensityFunction(x: 0.27); // 0.015773530285395465
            double lpdf = gamma.LogProbabilityDensityFunction(x: 0.27); // -4.1494220422235433
            double ccdf = gamma.ComplementaryDistributionFunction(x: 0.27); // 0.99782184175760935
            double icdf = gamma.InverseDistributionFunction(p: cdf); // 0.26999998689819171

            double hf = gamma.HazardFunction(x: 0.27); // 0.015807962529274005
            double chf = gamma.CumulativeHazardFunction(x: 0.27); // 0.0021805338793574793

            string str = gamma.ToString(CultureInfo.InvariantCulture); // "Γ(x; k = 2, θ = 4)"

            Assert.AreEqual(8.0, mean);
            Assert.AreEqual(6.7133878418421506, median, 1e-6);
            Assert.AreEqual(32.0, var);
            Assert.AreEqual(4.0, mode);
            Assert.AreEqual(0.0021805338793574793, chf);
            Assert.AreEqual(0.002178158242390601, cdf);
            Assert.AreEqual(0.015773530285395465, pdf);
            Assert.AreEqual(-4.1494220422235433, lpdf);
            Assert.AreEqual(0.015807962529274005, hf);
            Assert.AreEqual(0.99782184175760935, ccdf);
            Assert.AreEqual(0.26999998689819171, icdf, 1e-6);
            Assert.AreEqual("Γ(x; k = 2, θ = 4)", str);

            double p05 = gamma.DistributionFunction(median);
            Assert.AreEqual(0.5, p05, 1e-6);

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

            Assert.AreEqual(1.4214460427946485, range1.Min);
            Assert.AreEqual(18.975458073562308, range1.Max);
            Assert.AreEqual(0.59421896101306348, range2.Min);
            Assert.AreEqual(26.553408271975243, range2.Max);
            Assert.AreEqual(0.59421896101306348, range3.Min);
            Assert.AreEqual(26.553408271975243, range3.Max);
        }
        public void MedianTest()
        {
            double shape = 0.4;
            double scale = 4.2;

            GammaDistribution target = new GammaDistribution(scale, shape);

            Assert.AreEqual(target.Median, target.InverseDistributionFunction(0.5));
        }