/// <summary>
/// Run example
/// </summary>
/// <a href="http://en.wikipedia.org/wiki/Rayleigh_distribution">Rayleigh distribution</a>
public void Run()
{
// 1. Initialize the new instance of the Rayleigh distribution class with parameter Scale = 1.
var rayleigh = new Rayleigh(1);
Console.WriteLine(@"1. Initialize the new instance of the Rayleigh distribution class with parameter Scale = {0}", rayleigh.Scale);
Console.WriteLine();
// 2. Distributuion properties:
Console.WriteLine(@"2. {0} distributuion properties:", rayleigh);
// Cumulative distribution function
Console.WriteLine(@"{0} - Сumulative distribution at location '0.3'", rayleigh.CumulativeDistribution(0.3).ToString(" #0.00000;-#0.00000"));
// Probability density
Console.WriteLine(@"{0} - Probability density at location '0.3'", rayleigh.Density(0.3).ToString(" #0.00000;-#0.00000"));
// Log probability density
Console.WriteLine(@"{0} - Log probability density at location '0.3'", rayleigh.DensityLn(0.3).ToString(" #0.00000;-#0.00000"));
// Entropy
Console.WriteLine(@"{0} - Entropy", rayleigh.Entropy.ToString(" #0.00000;-#0.00000"));
// Largest element in the domain
Console.WriteLine(@"{0} - Largest element in the domain", rayleigh.Maximum.ToString(" #0.00000;-#0.00000"));
// Smallest element in the domain
Console.WriteLine(@"{0} - Smallest element in the domain", rayleigh.Minimum.ToString(" #0.00000;-#0.00000"));
// Mean
Console.WriteLine(@"{0} - Mean", rayleigh.Mean.ToString(" #0.00000;-#0.00000"));
// Median
Console.WriteLine(@"{0} - Median", rayleigh.Median.ToString(" #0.00000;-#0.00000"));
// Mode
Console.WriteLine(@"{0} - Mode", rayleigh.Mode.ToString(" #0.00000;-#0.00000"));
// Variance
Console.WriteLine(@"{0} - Variance", rayleigh.Variance.ToString(" #0.00000;-#0.00000"));
// Standard deviation
Console.WriteLine(@"{0} - Standard deviation", rayleigh.StdDev.ToString(" #0.00000;-#0.00000"));
// Skewness
Console.WriteLine(@"{0} - Skewness", rayleigh.Skewness.ToString(" #0.00000;-#0.00000"));
Console.WriteLine();
// 3. Generate 10 samples of the Rayleigh distribution
Console.WriteLine(@"3. Generate 10 samples of the Rayleigh distribution");
for (var i = 0; i < 10; i++)
{
Console.Write(rayleigh.Sample().ToString("N05") + @" ");
}
Console.WriteLine();
Console.WriteLine();
// 4. Generate 100000 samples of the Rayleigh(1) distribution and display histogram
Console.WriteLine(@"4. Generate 100000 samples of the Rayleigh(1) distribution and display histogram");
var data = new double[100000];
for (var i = 0; i < data.Length; i++)
{
data[i] = rayleigh.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 5. Generate 100000 samples of the Rayleigh(4) distribution and display histogram
Console.WriteLine(@"5. Generate 100000 samples of the Rayleigh(4) distribution and display histogram");
rayleigh.Scale = 4;
for (var i = 0; i < data.Length; i++)
{
data[i] = rayleigh.Sample();
}
ConsoleHelper.DisplayHistogram(data);
Console.WriteLine();
// 6. Generate 100000 samples of the Rayleigh(0.5) distribution and display histogram
Console.WriteLine(@"6. Generate 100000 samples of the Rayleigh(0.5) distribution and display histogram");
rayleigh.Scale = 0.5;
for (var i = 0; i < data.Length; i++)
{
data[i] = rayleigh.Sample();
}
ConsoleHelper.DisplayHistogram(data);
}
public void ValidateCumulativeDistribution([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double x)
{
var n = new Rayleigh(scale);
Assert.AreEqual(1.0 - Math.Exp(-x * x / (2.0 * scale * scale)), n.CumulativeDistribution(x));
}
public void ValidateCumulativeDistribution(double scale, double x)
{
var n = new Rayleigh(scale);
Assert.AreEqual<double>(1.0 - Math.Exp(-x * x / (2.0 * scale * scale)), n.CumulativeDistribution(x));
}
public void ValidateCumulativeDistribution(double scale, double x)
{
var n = new Rayleigh(scale);
Assert.AreEqual(1.0 - Math.Exp(-x * x / (2.0 * scale * scale)), n.CumulativeDistribution(x));
}
public void ValidateCumulativeDistribution([Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double scale, [Values(0.1, 1.0, 10.0, Double.PositiveInfinity)] double x)
{
var n = new Rayleigh(scale);
Assert.AreEqual(1.0 - Math.Exp(-x * x / (2.0 * scale * scale)), n.CumulativeDistribution(x));
}