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using System;
using MathNet.Numerics.Distributions;
namespace Examples.DiscreteDistributionsExamples
{
///
/// Hypergeometric distribution example
///
public class HypergeometricDistribution : IExample
{
///
/// Gets the name of this example
///
///
public string Name
{
get
{
return "Hypergeometric distribution";
}
}
///
/// Gets the description of this example
///
public string Description
{
get
{
return "Hypergeometric distribution properties and samples generating examples";
}
}
///
/// Run example
///
/// Hypergeometric distribution
public void Run()
{
// 1. Initialize the new instance of the Hypergeometric distribution class with parameters PopulationSize = 10, M = 2, N = 8
var hypergeometric = new Hypergeometric(30, 15, 10);
Console.WriteLine(@"1. Initialize the new instance of the Hypergeometric distribution class with parameters Population = {0}, Success = {1}, Draws = {2}", hypergeometric.Population, hypergeometric.Success, hypergeometric.Draws);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", hypergeometric);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '3'", hypergeometric.CumulativeDistribution(3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability mass at location '3'", hypergeometric.Probability(3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability mass at location '3'", hypergeometric.ProbabilityLn(3).ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", hypergeometric.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", hypergeometric.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", hypergeometric.Mean.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", hypergeometric.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", hypergeometric.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", hypergeometric.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", hypergeometric.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the Hypergeometric distribution
Console.WriteLine(@"3. Generate 10 samples of the Hypergeometric distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(hypergeometric.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the Hypergeometric(30, 15, 10) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the Hypergeometric(30, 15, 10) distribution and display histogram");
var data = new int[100000];
Hypergeometric.Samples(data, 30, 15, 10);
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the Hypergeometric(52, 13, 5) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the Hypergeometric(52, 13, 5) distribution and display histogram");
Hypergeometric.Samples(data, 52, 13, 5);
ConsoleHelper.DisplayHistogram(data);
}
}
}