/// <summary>
        /// Run example
        /// </summary>
        /// <a href="http://en.wikipedia.org/wiki/Log-normal_distribution">LogNormal distribution</a>
        public void Run()
        {
            // 1. Initialize the new instance of the LogNormal distribution class with parameters Mu = 0, Sigma = 1
            var logNormal = new LogNormal(0, 1);
            Console.WriteLine(@"1. Initialize the new instance of the LogNormal distribution class with parameters Mu = {0}, Sigma = {1}", logNormal.Mu, logNormal.Sigma);
            Console.WriteLine();

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

            // 4. Generate 100000 samples of the LogNormal(0, 1) distribution and display histogram
            Console.WriteLine(@"4. Generate 100000 samples of the LogNormal(0, 1) distribution and display histogram");
            var data = new double[100000];
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = logNormal.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 5. Generate 100000 samples of the LogNormal(0, 0.5) distribution and display histogram
            Console.WriteLine(@"5. Generate 100000 samples of the LogNormal(0, 0.5) distribution and display histogram");
            logNormal.Sigma = 0.5;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = logNormal.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 6. Generate 100000 samples of the LogNormal(5, 0.25) distribution and display histogram
            Console.WriteLine(@"6. Generate 100000 samples of the LogNormal(5, 0.25) distribution and display histogram");
            logNormal.Mu = 5;
            logNormal.Sigma = 0.25;
            for (var i = 0; i < data.Length; i++)
            {
                data[i] = logNormal.Sample();
            }

            ConsoleHelper.DisplayHistogram(data);
        }
 public void CanSample()
 {
     var n = new LogNormal(1.0, 2.0);
     n.Sample();
 }