ProbabilityDensityFunction() public method

Gets the probability density function (pdf) for the χ² distribution evaluated at point x.

The Probability Density Function (PDF) describes the probability that a given value x will occur.

References: http://www.mathworks.com/access/helpdesk/help/toolbox/stats/chi2pdf.html

public ProbabilityDensityFunction ( double x ) : double
x double
return double
        public void ConstructorTest()
        {
            var chisq = new ChiSquareDistribution(degreesOfFreedom: 7);

            double mean = chisq.Mean;     // 7
            double median = chisq.Median; // 6.345811195595612
            double var = chisq.Variance;  // 14

            double cdf = chisq.DistributionFunction(x: 6.27); // 0.49139966433823956
            double pdf = chisq.ProbabilityDensityFunction(x: 6.27); // 0.11388708001184455
            double lpdf = chisq.LogProbabilityDensityFunction(x: 6.27); // -2.1725478476948092

            double ccdf = chisq.ComplementaryDistributionFunction(x: 6.27); // 0.50860033566176044
            double icdf = chisq.InverseDistributionFunction(p: cdf); // 6.2700000000852318

            double hf = chisq.HazardFunction(x: 6.27); // 0.22392254197721179
            double chf = chisq.CumulativeHazardFunction(x: 6.27); // 0.67609276602233315

            string str = chisq.ToString(); // "χ²(x; df = 7)

            Assert.AreEqual(7, mean);
            Assert.AreEqual(6.345811195595612, median, 1e-6);
            Assert.AreEqual(14, var);
            Assert.AreEqual(0.67609276602233315, chf);
            Assert.AreEqual(0.49139966433823956, cdf);
            Assert.AreEqual(0.11388708001184455, pdf);
            Assert.AreEqual(-2.1725478476948092, lpdf);
            Assert.AreEqual(0.22392254197721179, hf);
            Assert.AreEqual(0.50860033566176044, ccdf);
            Assert.AreEqual(6.2700000000852318, icdf, 1e-6);
            Assert.AreEqual("χ²(x; df = 7)", str);
        }
        public void ConstructorTest()
        {
            var chisq = new ChiSquareDistribution(degreesOfFreedom: 7);

            double mean = chisq.Mean;     // 7
            double median = chisq.Median; // 6.345811195595612
            double var = chisq.Variance;  // 14
            double mode = chisq.Mode;     // 5.0

            double cdf = chisq.DistributionFunction(x: 6.27); // 0.49139966433823956
            double pdf = chisq.ProbabilityDensityFunction(x: 6.27); // 0.11388708001184455
            double lpdf = chisq.LogProbabilityDensityFunction(x: 6.27); // -2.1725478476948092

            double ccdf = chisq.ComplementaryDistributionFunction(x: 6.27); // 0.50860033566176044
            double icdf = chisq.InverseDistributionFunction(p: cdf); // 6.2700000000852318

            double hf = chisq.HazardFunction(x: 6.27); // 0.22392254197721179
            double chf = chisq.CumulativeHazardFunction(x: 6.27); // 0.67609276602233315

            string str = chisq.ToString(); // "χ²(x; df = 7)

            Assert.AreEqual(7, mean);
            Assert.AreEqual(6.345811195595612, median, 1e-6);
            Assert.AreEqual(14, var);
            Assert.AreEqual(5.0, mode);
            Assert.AreEqual(0.67609276602233315, chf);
            Assert.AreEqual(0.49139966433823956, cdf);
            Assert.AreEqual(0.11388708001184455, pdf);
            Assert.AreEqual(-2.1725478476948092, lpdf);
            Assert.AreEqual(0.22392254197721179, hf);
            Assert.AreEqual(0.50860033566176044, ccdf);
            Assert.AreEqual(6.2700000000852318, icdf, 1e-6);
            Assert.AreEqual("χ²(x; df = 7)", str);

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

            Assert.AreEqual(2.1673499092980579, range1.Min);
            Assert.AreEqual(14.067140449340167, range1.Max);
            Assert.AreEqual(1.2390423055679316, range2.Min);
            Assert.AreEqual(18.475306906582361, range2.Max);
            Assert.AreEqual(1.2390423055679316, range3.Min);
            Assert.AreEqual(18.475306906582361, range3.Max);
        }
        public void LogProbabilityDensityFunctionTest()
        {
            int degreesOfFreedom;
            double actual, expected, x;
            ChiSquareDistribution target;

            degreesOfFreedom = 1;
            target = new ChiSquareDistribution(degreesOfFreedom);
            x = 1;
            actual = target.LogProbabilityDensityFunction(x);
            expected = System.Math.Log(target.ProbabilityDensityFunction(x));
            Assert.AreEqual(expected, actual, 1e-10);

            degreesOfFreedom = 2;
            target = new ChiSquareDistribution(degreesOfFreedom);
            x = 2;
            actual = target.LogProbabilityDensityFunction(x);
            expected = System.Math.Log(target.ProbabilityDensityFunction(x));
            Assert.AreEqual(expected, actual, 1e-10);

            degreesOfFreedom = 10;
            target = new ChiSquareDistribution(degreesOfFreedom);
            x = 2;
            actual = target.LogProbabilityDensityFunction(x);
            expected = System.Math.Log(target.ProbabilityDensityFunction(x));
            Assert.AreEqual(expected, actual, 1e-10);
        }
        public void ProbabilityDensityFunctionTest()
        {
            int degreesOfFreedom;
            double actual, expected, x;
            ChiSquareDistribution target;

            degreesOfFreedom = 1;
            target = new ChiSquareDistribution(degreesOfFreedom);
            x = 1;
            actual = target.ProbabilityDensityFunction(x);
            expected = 0.2420;
            Assert.AreEqual(expected, actual, 1e-4);

            degreesOfFreedom = 2;
            target = new ChiSquareDistribution(degreesOfFreedom);
            x = 2;
            actual = target.ProbabilityDensityFunction(x);
            expected = 0.1839;
            Assert.AreEqual(expected, actual, 1e-4);

            degreesOfFreedom = 10;
            target = new ChiSquareDistribution(degreesOfFreedom);
            x = 2;
            actual = target.ProbabilityDensityFunction(x);
            expected = 0.0077;
            Assert.AreEqual(expected, actual, 1e-4);
        }
        public void ConstructorTest10()
        {
            var original = new ChiSquareDistribution(degreesOfFreedom: 7);

            var chisq = GeneralContinuousDistribution.FromDistributionFunction(
                original.Support, original.DistributionFunction);

            for (double i = -10; i < +10; i += 0.1)
            {
                double expected = original.ProbabilityDensityFunction(i);
                double actual = chisq.ProbabilityDensityFunction(i);

                Assert.IsTrue(expected.IsRelativelyEqual(actual, 1e-7));
                Assert.IsFalse(Double.IsNaN(actual));
                Assert.IsFalse(Double.IsNaN(expected));
            }

            testChiSquare(chisq);
        }