InverseDistributionFunction() public méthode

Gets the inverse of the cumulative distribution function (icdf) for this distribution evaluated at probability p. This function is also known as the Quantile function.
The Inverse Cumulative Distribution Function (ICDF) specifies, for a given probability, the value which the random variable will be at, or below, with that probability.
public InverseDistributionFunction ( double p ) : double
p double A probability value between 0 and 1.
Résultat double
PowerNormalDistribution Class Documentation
Exemple #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);
        }
Exemple #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);
        }