public void ValidateDensityLn(double a, double b, double x, double pdfln) { var n = new Beta(a, b); AssertHelpers.AlmostEqualRelative(pdfln, n.DensityLn(x), 13); AssertHelpers.AlmostEqualRelative(pdfln, Beta.PDFLn(a, b, x), 13); }
public void ValidateBetaSpecialCaseDensityLn(double x) { var d = new Dirichlet(new[] { 0.1, 0.3 }); var beta = new Beta(0.1, 0.3); AssertHelpers.AlmostEqualRelative(d.DensityLn(new[] { x }), beta.DensityLn(x), 10); }
public void ValidateDensityLn( [Values(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 9.0, 9.0, 9.0, 9.0, 9.0, 5.0, 5.0, 5.0, 1.0, 1.0, 1.0, Double.PositiveInfinity, Double.PositiveInfinity, Double.PositiveInfinity, 0.0, 0.0, 0.0, Double.PositiveInfinity, Double.PositiveInfinity, Double.PositiveInfinity)] double a, [Values(0.0, 0.0, 0.0, 0.1, 0.1, 0.1, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 100, 100, 100, Double.PositiveInfinity, Double.PositiveInfinity, Double.PositiveInfinity, 1.0, 1.0, 1.0, Double.PositiveInfinity, Double.PositiveInfinity, Double.PositiveInfinity, 0.0, 0.0, 0.0)] double b, [Values(0.0, 0.5, 1.0, 0.0, 0.5, 1.0, 0.0, 0.5, 1.0, 0.0, 0.5, 1.0, 0.0, 0.5, 1.0, -1.0, 2.0, 0.0, 0.5, 1.0, 0.0, 0.5, 1.0, 0.0, 0.5, 1.0, 0.0, 0.5, 1.0, 0.0, 0.5, 1.0)] double x, [Values(Double.PositiveInfinity, Double.NegativeInfinity, Double.PositiveInfinity, Double.PositiveInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.PositiveInfinity, 0.0, 0.0, 0.0, Double.NegativeInfinity, -3.3479528671433430925473664978203611353090199592365458, 2.1972245773362193827904904738450514092949811156454996, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, -51.447830024537682154565870837960406410586196074573801, Double.NegativeInfinity, Double.PositiveInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.PositiveInfinity, Double.PositiveInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.NegativeInfinity, Double.PositiveInfinity)] double pdfln) { var n = new Beta(a, b); AssertHelpers.AlmostEqual(pdfln, n.DensityLn(x), 14); }
/// <summary> /// Run example /// </summary> /// <a href="http://en.wikipedia.org/wiki/Beta_distribution">Beta distribution</a> public void Run() { // 1. Initialize the new instance of the Beta distribution class with parameters a = 5 and b = 1. var beta = new Beta(5, 1); Console.WriteLine(@"1. Initialize the new instance of the Beta distribution class with parameters a = {0} and b = {1}", beta.A, beta.B); Console.WriteLine(); // 2. Distributuion properties: Console.WriteLine(@"2. {0} distributuion properties:", beta); // Cumulative distribution function Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", beta.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000")); // Probability density Console.WriteLine(@"{0} - Probability density at location '0.3'", beta.Density(0.3).ToString(" #0.00000;-#0.00000")); // Log probability density Console.WriteLine(@"{0} - Log probability density at location '0.3'", beta.DensityLn(0.3).ToString(" #0.00000;-#0.00000")); // Entropy Console.WriteLine(@"{0} - Entropy", beta.Entropy.ToString(" #0.00000;-#0.00000")); // Largest element in the domain Console.WriteLine(@"{0} - Largest element in the domain", beta.Maximum.ToString(" #0.00000;-#0.00000")); // Smallest element in the domain Console.WriteLine(@"{0} - Smallest element in the domain", beta.Minimum.ToString(" #0.00000;-#0.00000")); // Mean Console.WriteLine(@"{0} - Mean", beta.Mean.ToString(" #0.00000;-#0.00000")); // Mode Console.WriteLine(@"{0} - Mode", beta.Mode.ToString(" #0.00000;-#0.00000")); // Variance Console.WriteLine(@"{0} - Variance", beta.Variance.ToString(" #0.00000;-#0.00000")); // Standard deviation Console.WriteLine(@"{0} - Standard deviation", beta.StdDev.ToString(" #0.00000;-#0.00000")); // Skewness Console.WriteLine(@"{0} - Skewness", beta.Skewness.ToString(" #0.00000;-#0.00000")); Console.WriteLine(); // 3. Generate 10 samples of the Beta distribution Console.WriteLine(@"3. Generate 10 samples of the Beta distribution"); for (var i = 0; i < 10; i++) { Console.Write(beta.Sample().ToString("N05") + @" "); } Console.WriteLine(); Console.WriteLine(); // 4. Generate 100000 samples of the Beta(5, 1) distribution and display histogram Console.WriteLine(@"4. Generate 100000 samples of the Beta(5, 1) distribution and display histogram"); var data = new double[100000]; for (var i = 0; i < data.Length; i++) { data[i] = beta.Sample(); } ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 5. Generate 100000 samples of the Beta(2, 5) distribution and display histogram Console.WriteLine(@"5. Generate 100000 samples of the Beta(2, 5) distribution and display histogram"); beta.A = 2; beta.B = 5; for (var i = 0; i < data.Length; i++) { data[i] = beta.Sample(); } ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 6. Generate 100000 samples of the Beta distribution and display histogram Console.WriteLine(@"6. Generate 100000 samples of the Beta(0.5, 0.5) distribution and display histogram"); beta.A = 0.5; beta.B = 0.5; for (var i = 0; i < data.Length; i++) { data[i] = beta.Sample(); } ConsoleHelper.DisplayHistogram(data); Console.WriteLine(); // 7. Generate 100000 samples of the Beta distribution and display histogram Console.WriteLine(@"7. Generate 100000 samples of the Beta(2, 2) distribution and display histogram"); beta.A = 2; beta.B = 2; for (var i = 0; i < data.Length; i++) { data[i] = beta.Sample(); } ConsoleHelper.DisplayHistogram(data); }
public void ValidateDensityLn(double a, double b, double x, double pdfln) { var n = new Beta(a, b); AssertHelpers.AlmostEqual(pdfln, n.DensityLn(x), 14); }
public void ValidateBetaSpecialCaseDensityLn(double x) { var d = new Dirichlet(new[] { 0.1, 0.3 }); var beta = new Beta(0.1, 0.3); AssertHelpers.AlmostEqual(d.DensityLn(new[] { x }), beta.DensityLn(x), 10); }