/// <summary>
        /// Run example
        /// </summary>
        /// <a href="http://en.wikipedia.org/wiki/Gamma_distribution">Gamma distribution</a>
        public void Run()
        {
            // 1. Initialize the new instance of the Gamma distribution class with parameter Shape = 1, Scale = 0.5.
            var gamma = new Gamma(1, 2.0);
            Console.WriteLine(@"1. Initialize the new instance of the Gamma distribution class with parameters Shape = {0}, Scale = {1}", gamma.Shape, gamma.Scale);
            Console.WriteLine();

            // 2. Distributuion properties:
            Console.WriteLine(@"2. {0} distributuion properties:", gamma);

            // Cumulative distribution function
            Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", gamma.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));

            // Probability density
            Console.WriteLine(@"{0} - Probability density at location '0.3'", gamma.Density(0.3).ToString(" #0.00000;-#0.00000"));

            // Log probability density
            Console.WriteLine(@"{0} - Log probability density at location '0.3'", gamma.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));

            // Entropy
            Console.WriteLine(@"{0} - Entropy", gamma.Entropy.ToString(" #0.00000;-#0.00000"));

            // Largest element in the domain
            Console.WriteLine(@"{0} - Largest element in the domain", gamma.Maximum.ToString(" #0.00000;-#0.00000"));

            // Smallest element in the domain
            Console.WriteLine(@"{0} - Smallest element in the domain", gamma.Minimum.ToString(" #0.00000;-#0.00000"));

            // Mean
            Console.WriteLine(@"{0} - Mean", gamma.Mean.ToString(" #0.00000;-#0.00000"));

            // Mode
            Console.WriteLine(@"{0} - Mode", gamma.Mode.ToString(" #0.00000;-#0.00000"));

            // Variance
            Console.WriteLine(@"{0} - Variance", gamma.Variance.ToString(" #0.00000;-#0.00000"));

            // Standard deviation
            Console.WriteLine(@"{0} - Standard deviation", gamma.StdDev.ToString(" #0.00000;-#0.00000"));

            // Skewness
            Console.WriteLine(@"{0} - Skewness", gamma.Skewness.ToString(" #0.00000;-#0.00000"));
            Console.WriteLine();

            // 3. Generate 10 samples of the Gamma distribution
            Console.WriteLine(@"3. Generate 10 samples of the Gamma distribution");
            for (var i = 0; i < 10; i++)
            {
                Console.Write(gamma.Sample().ToString("N05") + @" ");
            }

            Console.WriteLine();
            Console.WriteLine();

            // 4. Generate 100000 samples of the Gamma(1, 2) distribution and display histogram
            Console.WriteLine(@"4. Generate 100000 samples of the Gamma(1, 2) distribution and display histogram");
            var data = new double[100000];
            Gamma.Samples(data, 1, 2);
            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 5. Generate 100000 samples of the Gamma(8) distribution and display histogram
            Console.WriteLine(@"5. Generate 100000 samples of the Gamma(5, 1) distribution and display histogram");
            Gamma.Samples(data, 5, 1);
            ConsoleHelper.DisplayHistogram(data);
        }
 public void ValidateDensityLn(int shape, double invScale, double x, double pdfln)
 {
     var n = new Gamma(shape, invScale);
     AssertHelpers.AlmostEqualRelative(pdfln, n.DensityLn(x), 13);
     AssertHelpers.AlmostEqualRelative(pdfln, Gamma.PDFLn(shape, invScale, x), 13);
 }
 public void ValidateDensityLn(double shape, double invScale, double x, double pdfln)
 {
     var n = new Gamma(shape, invScale);
     AssertHelpers.AlmostEqual(pdfln, n.DensityLn(x), 14);
 }