public void CanSampleSequence() { var n = new FisherSnedecor(1.0, 2.0); var ied = n.Samples(); ied.Take(5).ToArray(); }
private double F(double a, double d1, double d2) { var fisher = new FisherSnedecor(d1, d2); var arr = new double[10000]; fisher.Samples(arr); return(Statistics.Quantile(arr, a)); }
public static double[] fisher(double v1, double v2, int num) { var t = new FisherSnedecor(v1, v2); double[] ret = new double[num]; t.Samples(ret); return(ret); }
/// <summary> /// Run example /// </summary> /// <a href="http://en.wikipedia.org/wiki/F-distribution">FisherSnedecor distribution</a> public void Run() { // 1. Initialize the new instance of the FisherSnedecor distribution class with parameter DegreesOfFreedom1 = 50, DegreesOfFreedom2 = 20. var fisherSnedecor = new FisherSnedecor(50, 20); Console.WriteLine(@"1. Initialize the new instance of the FisherSnedecor distribution class with parameters DegreesOfFreedom1 = {0}, DegreesOfFreedom2 = {1}", fisherSnedecor.DegreesOfFreedom1, fisherSnedecor.DegreesOfFreedom2); Console.WriteLine(); // 2. Distributuion properties: Console.WriteLine(@"2. {0} distributuion properties:", fisherSnedecor); // Cumulative distribution function Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", fisherSnedecor.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000")); // Probability density Console.WriteLine(@"{0} - Probability density at location '0.3'", fisherSnedecor.Density(0.3).ToString(" #0.00000;-#0.00000")); // Log probability density Console.WriteLine(@"{0} - Log probability density at location '0.3'", fisherSnedecor.DensityLn(0.3).ToString(" #0.00000;-#0.00000")); // Largest element in the domain Console.WriteLine(@"{0} - Largest element in the domain", fisherSnedecor.Maximum.ToString(" #0.00000;-#0.00000")); // Smallest element in the domain Console.WriteLine(@"{0} - Smallest element in the domain", fisherSnedecor.Minimum.ToString(" #0.00000;-#0.00000")); // Mean Console.WriteLine(@"{0} - Mean", fisherSnedecor.Mean.ToString(" #0.00000;-#0.00000")); // Mode Console.WriteLine(@"{0} - Mode", fisherSnedecor.Mode.ToString(" #0.00000;-#0.00000")); // Variance Console.WriteLine(@"{0} - Variance", fisherSnedecor.Variance.ToString(" #0.00000;-#0.00000")); // Standard deviation Console.WriteLine(@"{0} - Standard deviation", fisherSnedecor.StdDev.ToString(" #0.00000;-#0.00000")); // Skewness Console.WriteLine(@"{0} - Skewness", fisherSnedecor.Skewness.ToString(" #0.00000;-#0.00000")); Console.WriteLine(); // 3. Generate 10 samples of the FisherSnedecor distribution Console.WriteLine(@"3. Generate 10 samples of the FisherSnedecor distribution"); for (var i = 0; i < 10; i++) { Console.Write(fisherSnedecor.Sample().ToString("N05") + @" "); } Console.WriteLine(); Console.WriteLine(); // 4. Generate 100000 samples of the FisherSnedecor(50, 20) distribution and display histogram Console.WriteLine(@"4. Generate 100000 samples of the FisherSnedecor(50, 20) distribution and display histogram"); var data = new double[100000]; FisherSnedecor.Samples(data, 50, 20); ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 5. Generate 100000 samples of the FisherSnedecor(20, 10) distribution and display histogram Console.WriteLine(@"5. Generate 100000 samples of the FisherSnedecor(20, 10) distribution and display histogram"); FisherSnedecor.Samples(data, 20, 10); ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 6. Generate 100000 samples of the FisherSnedecor(100, 100) distribution and display histogram Console.WriteLine(@"6. Generate 100000 samples of the FisherSnedecor(100, 100) distribution and display histogram"); FisherSnedecor.Samples(data, 100, 100); ConsoleHelper.DisplayHistogram(data); }