/// <summary>
/// Estimates a new Gamma distribution from a given set of observations.
/// </summary>
///
public static GammaDistribution Estimate(double[] observations, double[] weights)
{
var n = new GammaDistribution();
n.Fit(observations, weights, null);
return(n);
}
/// <summary>
/// Generates a random observation from the
/// F-distribution with the given parameters.
/// </summary>
///
/// <param name="d1">The first degree of freedom.</param>
/// <param name="d2">The second degree of freedom.</param>
///
/// <returns>A random double value sampled from the specified F-distribution.</returns>
///
public static double Random(int d1, int d2)
{
double x = GammaDistribution.Random(shape: d1 / 2.0, scale: 2);
double y = GammaDistribution.Random(shape: d2 / 2.0, scale: 2);
return(x / y);
}
/// <summary>
/// Generates a random vector of observations from the
/// Nakagami distribution with the given parameters.
/// </summary>
///
/// <param name="shape">The shape parameter μ.</param>
/// <param name="spread">The spread parameter ω.</param>
/// <param name="samples">The number of samples to generate.</param>
///
/// <returns>An array of double values sampled from the specified Nakagami distribution.</returns>
///
public static double[] Random(double shape, double spread, int samples)
{
double[] g = GammaDistribution.Random(shape: shape, scale: spread / shape, samples: samples);
for (int i = 0; i < g.Length; i++)
{
g[i] = Math.Sqrt(g[i]);
}
return(g);
}
/// <summary>
/// Generates a random vector of observations from the
/// F-distribution with the given parameters.
/// </summary>
///
/// <param name="d1">The first degree of freedom.</param>
/// <param name="d2">The second degree of freedom.</param>
/// <param name="samples">The number of samples to generate.</param>
///
/// <returns>An array of double values sampled from the specified F-distribution.</returns>
///
public static double[] Random(int d1, int d2, int samples)
{
double[] x = GammaDistribution.Random(shape: d1 / 2.0, scale: 2, samples: samples);
double[] y = GammaDistribution.Random(shape: d2 / 2.0, scale: 2, samples: samples);
for (int i = 0; i < x.Length; i++)
{
x[i] = x[i] / y[i];
}
return(x);
}
/// <summary>
/// Generates a random observation from the
/// Nakagami distribution with the given parameters.
/// </summary>
///
/// <param name="shape">The shape parameter μ.</param>
/// <param name="spread">The spread parameter ω.</param>
///
/// <returns>A random double value sampled from the specified Nakagami distribution.</returns>
///
public static double Random(double shape, double spread)
{
double g = GammaDistribution.Random(shape: shape, scale: spread / shape);
return(Math.Sqrt(g));
}
/// <summary>
/// Generates a random observation from the
/// Chi-Square distribution with the given parameters.
/// </summary>
///
/// <param name="degreesOfFreedom">The degrees of freedom for the distribution.</param>
///
/// <returns>A random double value sampled from the specified Chi-Square distribution.</returns>
///
public static double Random(int degreesOfFreedom)
{
return(GammaDistribution.Random(shape: degreesOfFreedom / 2.0, scale: 2));
}
/// <summary>
/// Generates a random vector of observations from the
/// Chi-Square distribution with the given parameters.
/// </summary>
///
/// <returns>An array of double values sampled from the specified Chi-Square distribution.</returns>
///
public static double[] Random(int degreesOfFreedom, int samples)
{
return(GammaDistribution.Random(shape: degreesOfFreedom / 2.0, scale: 2, samples: samples));
}
/// <summary>
/// Generates a random observation from the current distribution.
/// </summary>
///
/// <returns>A random observations drawn from this distribution.</returns>
///
public override double Generate()
{
return(GammaDistribution.Random(shape: degreesOfFreedom / 2.0, scale: 2));
}
/// <summary>
/// Generates a random vector of observations from the current distribution.
/// </summary>
///
/// <param name="samples">The number of samples to generate.</param>
/// <returns>A random vector of observations drawn from this distribution.</returns>
///
public override double[] Generate(int samples)
{
return(GammaDistribution.Random(shape: degreesOfFreedom / 2.0, scale: 2, samples: samples));
}
