LogProbabilityDensityFunction() публичный Метод

Gets the log-probability density function (pdf) for this distribution evaluated at point x.
The Probability Density Function (PDF) describes the probability that a given value x will occur.
public LogProbabilityDensityFunction ( double x ) : double
x double /// A single point in the distribution range.
Результат double
Документация по классу PowerNormalDistribution
Пример #1
0
        public void ConstructorTest1()
        {
            var pnormal = new PowerNormalDistribution(power: 4.2);


            double cdf = pnormal.DistributionFunction(x: 1.4); // 0.99997428721920678
            double pdf = pnormal.ProbabilityDensityFunction(x: 1.4); // 0.00020022645890003279
            double lpdf = pnormal.LogProbabilityDensityFunction(x: 1.4); // -0.20543269836728234

            double ccdf = pnormal.ComplementaryDistributionFunction(x: 1.4); // 0.000025712780793218926
            double icdf = pnormal.InverseDistributionFunction(p: cdf); // 1.3999999999998953

            double hf = pnormal.HazardFunction(x: 1.4); // 7.7870402470368854
            double chf = pnormal.CumulativeHazardFunction(x: 1.4); // 10.568522382550167

            string str = pnormal.ToString(CultureInfo.InvariantCulture); // PND(x; p = 4.2)

            Assert.AreEqual(10.568522382550167, chf);
            Assert.AreEqual(0.99997428721920678, cdf);
            Assert.AreEqual(0.00020022645890003279, pdf);
            Assert.AreEqual(-0.20543269836728234, lpdf);
            Assert.AreEqual(7.7870402470368854, hf);
            Assert.AreEqual(0.000025712780793218926, ccdf);
            Assert.AreEqual(1.3999999999998953, icdf);
            Assert.AreEqual("PND(x; p = 4.2)", str);
        }
Пример #2
0
        public void ConstructorTest1()
        {
            var pnormal = new PowerNormalDistribution(power: 4.2);

            try { double mean = pnormal.Mean; Assert.Fail(); }
            catch { }
            try { double variance = pnormal.Variance; Assert.Fail(); }
            catch { }
            try { double mode = pnormal.Mode; Assert.Fail(); }
            catch { }
            try { double median = pnormal.Median; Assert.Fail(); }
            catch { }

            double cdf = pnormal.DistributionFunction(x: 1.4); // 0.99997428721920678
            double pdf = pnormal.ProbabilityDensityFunction(x: 1.4); // 0.00020022645890003279
            double lpdf = pnormal.LogProbabilityDensityFunction(x: 1.4); // -0.20543269836728234

            double ccdf = pnormal.ComplementaryDistributionFunction(x: 1.4); // 0.000025712780793218926
            double icdf = pnormal.InverseDistributionFunction(p: cdf); // 1.3999999999998953

            double hf = pnormal.HazardFunction(x: 1.4); // 7.7870402470368854
            double chf = pnormal.CumulativeHazardFunction(x: 1.4); // 10.568522382550167

            string str = pnormal.ToString(CultureInfo.InvariantCulture); // PND(x; p = 4.2)

            Assert.AreEqual(10.568522382550167, chf);
            Assert.AreEqual(0.99997428721920678, cdf);
            Assert.AreEqual(0.00020022645890003279, pdf);
            Assert.AreEqual(-0.20543269836728234, lpdf);
            Assert.AreEqual(7.7870402470368854, hf);
            Assert.AreEqual(0.000025712780793218926, ccdf);
            Assert.AreEqual(1.3999999999998953, icdf);
            Assert.AreEqual("PND(x; p = 4.2)", str);

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

            Assert.AreEqual(-2.2527196079209415, range1.Min);
            Assert.AreEqual(0.024970246427532511, range1.Max);
            Assert.AreEqual(-2.8214873257900464, range2.Min);
            Assert.AreEqual(0.42876122902825864, range2.Max);
            Assert.AreEqual(-2.8214873257900464, range3.Min);
            Assert.AreEqual(0.42876122902825864, range3.Max);
        }