Esempio n. 1
0
 public void ConstructorTest()
 {
     WeibullDistribution n = new WeibullDistribution(0.807602, 12.5);
     Assert.AreEqual(14.067993598321863, n.Mean);
     Assert.AreEqual(17.552908226174811, n.StandardDeviation);
     Assert.IsFalse(Double.IsNaN(n.Mean));
     Assert.IsFalse(Double.IsNaN(n.Variance));
 }
        public void ConstructorTest2()
        {
            var weilbull = new WeibullDistribution(scale: 0.42, shape: 1.2);

            double mean = weilbull.Mean;     // 0.39507546046784414
            double median = weilbull.Median; // 0.30945951550913292
            double var = weilbull.Variance;  // 0.10932249666369542
            double mode = weilbull.Mode;     // 0.094360430821809421

            double cdf = weilbull.DistributionFunction(x: 1.4); // 0.98560487188700052
            double pdf = weilbull.ProbabilityDensityFunction(x: 1.4); // 0.052326687031379278
            double lpdf = weilbull.LogProbabilityDensityFunction(x: 1.4); // -2.9502487697674415

            double ccdf = weilbull.ComplementaryDistributionFunction(x: 1.4); // 0.22369885565908001
            double icdf = weilbull.InverseDistributionFunction(p: cdf); // 1.400000001051205

            double hf = weilbull.HazardFunction(x: 1.4); // 1.1093328057258516
            double chf = weilbull.CumulativeHazardFunction(x: 1.4); // 1.4974545260150962

            string str = weilbull.ToString(CultureInfo.InvariantCulture); // Weibull(x; λ = 0.42, k = 1.2)

            double imedian = weilbull.InverseDistributionFunction(p: 0.5);

            Assert.AreEqual(0.39507546046784414, mean);
            Assert.AreEqual(0.30945951550913292, median);
            Assert.AreEqual(0.094360430821809421, mode, 1e-10);
            Assert.AreEqual(0.3094595, imedian, 1e-5);
            Assert.AreEqual(0.10932249666369542, var);
            Assert.AreEqual(1.4974545260150962, chf);
            Assert.AreEqual(0.98560487188700052, cdf);
            Assert.AreEqual(0.052326687031379278, pdf);
            Assert.AreEqual(-2.9502487697674415, lpdf);
            Assert.AreEqual(1.1093328057258516, hf);
            Assert.AreEqual(0.22369885565908001, ccdf);
            Assert.AreEqual(1.40, icdf, 1e-6);
            Assert.AreEqual("Weibull(x; λ = 0.42, k = 1.2)", str);

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

            Assert.AreEqual(0.035342687605397792, range1.Min);
            Assert.AreEqual(1.0479366931850318, range1.Max);
            Assert.AreEqual(0.0090865355213001313, range2.Min);
            Assert.AreEqual(1.4995260942223139, range2.Max);
            Assert.AreEqual(0.0090865355213001677, range3.Min);
            Assert.AreEqual(1.4995260942223139, range3.Max);
        }
Esempio n. 3
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        public void ProbabilityDistributionTest()
        {
            WeibullDistribution n = new WeibullDistribution(0.80, 12.5);

            double[] expected = 
            {
                0.0,
                0.09289322,
                0.0733005, 
                0.06186956, 
                0.0537782,
                0.0475457 
            };

            double[] actual = new double[expected.Length];

            for (int i = 0; i < actual.Length; i++)
                actual[i] = n.ProbabilityDensityFunction(i);

            for (int i = 0; i < actual.Length; i++)
            {
                Assert.AreEqual(expected[i], actual[i], 1e-5);
                Assert.IsFalse(double.IsNaN(actual[i]));
            }
        }
Esempio n. 4
0
        public void CumulativeDistributionTest()
        {
            WeibullDistribution n = new WeibullDistribution(0.80, 12.5);

            double[] expected = 
            {
                Double.PositiveInfinity,
                0.1241655,
                0.2061272,
                0.2733265,
                0.3309536,
                0.3814949,
            };

            double[] actual = new double[expected.Length];

            for (int i = 0; i < actual.Length; i++)
                actual[i] = n.DistributionFunction(i);

            for (int i = 0; i < actual.Length; i++)
            {
                Assert.AreEqual(expected[i], actual[i], 1e-6);
                Assert.IsFalse(double.IsNaN(actual[i]));
            }
        }
        public void MedianTest()
        {
            WeibullDistribution target = new WeibullDistribution(1.52, 0.6);

            Assert.AreEqual(target.Median, target.InverseDistributionFunction(0.5), 1e-8);
        }