public void ValidateDensityLn(double d1, double d2, double x)
{
var n = new FisherSnedecor(d1, d2);
double expected = Math.Log(Math.Sqrt(Math.Pow(d1 * x, d1) * Math.Pow(d2, d2) / Math.Pow((d1 * x) + d2, d1 + d2)) / (x * SpecialFunctions.Beta(d1 / 2.0, d2 / 2.0)));
Assert.AreEqual(expected, n.DensityLn(x));
Assert.AreEqual(expected, FisherSnedecor.PDFLn(d1, d2, x));
}
public void ValidateDensityLn(
[Values(0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0)] double d1,
[Values(0.1, 0.1, 0.1, 0.1, 1.0, 1.0, 1.0, 1.0, 100.0, 100.0, 100.0, 100.0, 0.1, 0.1, 0.1, 0.1, 1.0, 1.0, 1.0, 1.0, 100.0, 100.0, 100.0, 100.0)] double d2,
[Values(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0)] double x)
{
var n = new FisherSnedecor(d1, d2);
Assert.AreEqual(Math.Log(n.Density(x)), n.DensityLn(x));
}
public void ValidateDensityLn(
[Values(0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0, 0.1, 1.0, 10.0, 100.0)] double d1,
[Values(0.1, 0.1, 0.1, 0.1, 1.0, 1.0, 1.0, 1.0, 100.0, 100.0, 100.0, 100.0, 0.1, 0.1, 0.1, 0.1, 1.0, 1.0, 1.0, 1.0, 100.0, 100.0, 100.0, 100.0)] double d2,
[Values(1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0, 10.0)] double x)
{
var n = new FisherSnedecor(d1, d2);
Assert.AreEqual(Math.Log(n.Density(x)), n.DensityLn(x));
}
/// <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 DegreeOfFreedom1 = 50, DegreeOfFreedom2 = 20.
var fisherSnedecor = new FisherSnedecor(50, 20);
Console.WriteLine(@"1. Initialize the new instance of the FisherSnedecor distribution class with parameters DegreeOfFreedom1 = {0}, DegreeOfFreedom2 = {1}", fisherSnedecor.DegreeOfFreedom1, fisherSnedecor.DegreeOfFreedom2);
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];
for (var i = 0; i < data.Length; i++)
{
data[i] = fisherSnedecor.Sample();
}
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.DegreeOfFreedom1 = 20;
fisherSnedecor.DegreeOfFreedom2 = 10;
for (var i = 0; i < data.Length; i++)
{
data[i] = fisherSnedecor.Sample();
}
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.DegreeOfFreedom1 = 100;
fisherSnedecor.DegreeOfFreedom2 = 100;
for (var i = 0; i < data.Length; i++)
{
data[i] = fisherSnedecor.Sample();
}
ConsoleHelper.DisplayHistogram(data);
}
public void ValidateDensityLn(double d1, double d2, double x)
{
var n = new FisherSnedecor(d1, d2);
Assert.AreEqual <double>(Math.Log(n.Density(x)), n.DensityLn(x));
}
public void ValidateDensityLn(double d1, double d2, double x)
{
var n = new FisherSnedecor(d1, d2);
Assert.AreEqual(Math.Log(n.Density(x)), n.DensityLn(x));
}