ProbabilityDensityFunction() public abstract method

Gets the 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 abstract ProbabilityDensityFunction ( double x ) : double
x double /// A single point in the distribution range.
return double
UnivariateContinuousDistribution Class Documentation
Exemplo n.º 1
0
        private static void test(GeneralizedNormalDistribution target, UnivariateContinuousDistribution normal)
        {

            Assert.AreEqual(normal.Mean, target.Mean);
            Assert.AreEqual(normal.Variance, target.Variance, 1e-10);
            Assert.AreEqual(normal.Entropy, target.Entropy, 1e-10);
            Assert.AreEqual(normal.StandardDeviation, target.StandardDeviation, 1e-10);
            Assert.AreEqual(normal.Mode, target.Mode);
            Assert.AreEqual(normal.Median, target.Median);

            for (double x = -10; x < 10; x += 0.0001)
            {
                double actual = target.ProbabilityDensityFunction(x);
                double expected = normal.ProbabilityDensityFunction(x);
                Assert.AreEqual(expected, actual, 1e-15);
                Assert.IsFalse(Double.IsNaN(actual));
            }

            for (double x = -10; x < 10; x += 0.0001)
            {
                double actual = target.LogProbabilityDensityFunction(x);
                double expected = normal.LogProbabilityDensityFunction(x);
                Assert.AreEqual(expected, actual, 1e-10);
                Assert.IsFalse(Double.IsNaN(actual));
            }
        }
Exemplo n.º 2
0
        private static void compare(TukeyLambdaDistribution target, 
            UnivariateContinuousDistribution comparison, double tol)
        {
            Assert.AreEqual(comparison.Mean, target.Mean);
            Assert.AreEqual(comparison.Variance, target.Variance, tol);
            Assert.AreEqual(comparison.Entropy, target.Entropy, 1e-4);
            Assert.AreEqual(comparison.StandardDeviation, target.StandardDeviation, tol);
            Assert.AreEqual(comparison.Mode, target.Mode);
            Assert.AreEqual(comparison.Median, target.Median);

            for (double x = -10; x < 10; x += 0.0001)
            {
                double actual = target.ProbabilityDensityFunction(x);
                double expected = comparison.ProbabilityDensityFunction(x);
                Assert.AreEqual(expected, actual, tol);
                Assert.IsFalse(Double.IsNaN(actual));
            }

            for (double x = -10; x < 10; x += 0.0001)
            {
                double actual = target.DistributionFunction(x);
                double expected = comparison.DistributionFunction(x);
                Assert.AreEqual(expected, actual, tol);
                Assert.IsFalse(Double.IsNaN(actual));
            }

            for (double x = -10; x < 10; x += 0.0001)
            {
                double actual = target.LogProbabilityDensityFunction(x);
                double expected = comparison.LogProbabilityDensityFunction(x);
                Assert.AreEqual(expected, actual, tol);
                Assert.IsFalse(Double.IsNaN(actual));
            }
        }