mathnet-numerics/examples/examples-csharp/DiscreteDistributions/ConwayMaxwellPoissonDistribution.cs

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using System;
using MathNet.Numerics.Distributions;

namespace Examples.DiscreteDistributionsExamples
{
    /// <summary>
    /// ConwayMaxwellPoisson distribution example
    /// </summary>
    public class ConwayMaxwellPoissonDistribution : IExample
    {
        /// <summary>
        /// Gets the name of this example
        /// </summary>
        public string Name
        {
            get
            {
                return "ConwayMaxwellPoisson distribution";
            }
        }

        /// <summary>
        /// Gets the description of this example
        /// </summary>
        public string Description
        {
            get
            {
                return "ConwayMaxwellPoisson distribution properties and samples generating examples";
            }
        }

        /// <summary>
        /// Run example
        /// </summary>
        /// <a href="http://en.wikipedia.org/wiki/Conway%E2%80%93Maxwell%E2%80%93Poisson_distribution">ConwayMaxwellPoisson distribution</a>
        public void Run()
        {
            // 1. Initialize the new instance of the ConwayMaxwellPoisson distribution class with parameters Lambda = 2, Nu = 1
            var conwayMaxwellPoisson = new ConwayMaxwellPoisson(2, 1);
            Console.WriteLine(@"1. Initialize the new instance of the ConwayMaxwellPoisson distribution class with parameters Lambda = {0}, Nu = {1}", conwayMaxwellPoisson.Lambda, conwayMaxwellPoisson.Nu);
            Console.WriteLine();

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

            // Cumulative distribution function
            Console.WriteLine(@"{0} - Сumulative distribution at location '3'", conwayMaxwellPoisson.CumulativeDistribution(3).ToString(" #0.00000;-#0.00000"));

            // Probability density
            Console.WriteLine(@"{0} - Probability mass at location '3'", conwayMaxwellPoisson.Probability(3).ToString(" #0.00000;-#0.00000"));

            // Log probability density
            Console.WriteLine(@"{0} - Log probability mass at location '3'", conwayMaxwellPoisson.ProbabilityLn(3).ToString(" #0.00000;-#0.00000"));

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

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

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

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

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

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

            // 5. Generate 100000 samples of the ConwayMaxwellPoisson(2, 1) distribution and display histogram
            Console.WriteLine(@"5. Generate 100000 samples of the ConwayMaxwellPoisson(2, 1) distribution and display histogram");
            ConwayMaxwellPoisson.Samples(data, 2, 1);
            ConsoleHelper.DisplayHistogram(data);
            Console.WriteLine();

            // 6. Generate 100000 samples of the ConwayMaxwellPoisson(5, 2) distribution and display histogram
            Console.WriteLine(@"6. Generate 100000 samples of the ConwayMaxwellPoisson(5, 2) distribution and display histogram");
            ConwayMaxwellPoisson.Samples(data, 5, 2);
            ConsoleHelper.DisplayHistogram(data);
        }
    }
}