public void CanSample() { var d = new ConwayMaxwellPoisson(1.0, 2.0); d.Sample(); }
/// <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 binomial = new ConwayMaxwellPoisson(2, 1); Console.WriteLine(@"1. Initialize the new instance of the ConwayMaxwellPoisson distribution class with parameters Lambda = {0}, Nu = {1}", binomial.Lambda, binomial.Nu); Console.WriteLine(); // 2. Distributuion properties: Console.WriteLine(@"2. {0} distributuion properties:", binomial); // Cumulative distribution function Console.WriteLine(@"{0} - Сumulative distribution at location '3'", binomial.CumulativeDistribution(3).ToString(" #0.00000;-#0.00000")); // Probability density Console.WriteLine(@"{0} - Probability mass at location '3'", binomial.Probability(3).ToString(" #0.00000;-#0.00000")); // Log probability density Console.WriteLine(@"{0} - Log probability mass at location '3'", binomial.ProbabilityLn(3).ToString(" #0.00000;-#0.00000")); // Smallest element in the domain Console.WriteLine(@"{0} - Smallest element in the domain", binomial.Minimum.ToString(" #0.00000;-#0.00000")); // Mean Console.WriteLine(@"{0} - Mean", binomial.Mean.ToString(" #0.00000;-#0.00000")); // Variance Console.WriteLine(@"{0} - Variance", binomial.Variance.ToString(" #0.00000;-#0.00000")); // Standard deviation Console.WriteLine(@"{0} - Standard deviation", binomial.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(binomial.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 double[100000]; for (var i = 0; i < data.Length; i++) { data[i] = binomial.Sample(); } 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"); binomial.Lambda = 2; for (var i = 0; i < data.Length; i++) { data[i] = binomial.Sample(); } 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"); binomial.Lambda = 5; binomial.Nu = 2; for (var i = 0; i < data.Length; i++) { data[i] = binomial.Sample(); } ConsoleHelper.DisplayHistogram(data); }