//
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using System;
using System.Collections.Generic;
using System.Linq;
using IStation.Numerics.Random;
using IStation.Numerics.Threading;
namespace IStation.Numerics.Distributions
{
///
/// Continuous Univariate Inverse Gamma distribution.
/// The inverse Gamma distribution is a distribution over the positive real numbers parameterized by
/// two positive parameters.
/// Wikipedia - InverseGamma distribution.
///
public class InverseGamma : IContinuousDistribution
{
System.Random _random;
readonly double _shape;
readonly double _scale;
///
/// Initializes a new instance of the class.
///
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
public InverseGamma(double shape, double scale)
{
if (!IsValidParameterSet(shape, scale))
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
_random = SystemRandomSource.Default;
_shape = shape;
_scale = scale;
}
///
/// Initializes a new instance of the class.
///
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// The random number generator which is used to draw random samples.
public InverseGamma(double shape, double scale, System.Random randomSource)
{
if (!IsValidParameterSet(shape, scale))
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
_random = randomSource ?? SystemRandomSource.Default;
_shape = shape;
_scale = scale;
}
///
/// A string representation of the distribution.
///
/// a string representation of the distribution.
public override string ToString()
{
return $"InverseGamma(α = {_shape}, β = {_scale})";
}
///
/// Tests whether the provided values are valid parameters for this distribution.
///
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
public static bool IsValidParameterSet(double shape, double scale)
{
return shape > 0.0 && scale > 0.0;
}
///
/// Gets or sets the shape (α) parameter. Range: α > 0.
///
public double Shape => _shape;
///
/// Gets or sets The scale (β) parameter. Range: β > 0.
///
public double Scale => _scale;
///
/// Gets or sets the random number generator which is used to draw random samples.
///
public System.Random RandomSource
{
get => _random;
set => _random = value ?? SystemRandomSource.Default;
}
///
/// Gets the mean of the distribution.
///
public double Mean
{
get
{
if (_shape <= 1)
{
throw new NotSupportedException();
}
return _scale/(_shape - 1.0);
}
}
///
/// Gets the variance of the distribution.
///
public double Variance
{
get
{
if (_shape <= 2)
{
throw new NotSupportedException();
}
return _scale*_scale/((_shape - 1.0)*(_shape - 1.0)*(_shape - 2.0));
}
}
///
/// Gets the standard deviation of the distribution.
///
public double StdDev => _scale/(Math.Abs(_shape - 1.0)*Math.Sqrt(_shape - 2.0));
///
/// Gets the entropy of the distribution.
///
public double Entropy => _shape + Math.Log(_scale) + SpecialFunctions.GammaLn(_shape) - ((1 + _shape)*SpecialFunctions.DiGamma(_shape));
///
/// Gets the skewness of the distribution.
///
public double Skewness
{
get
{
if (_shape <= 3)
{
throw new NotSupportedException();
}
return (4*Math.Sqrt(_shape - 2))/(_shape - 3);
}
}
///
/// Gets the mode of the distribution.
///
public double Mode => _scale/(_shape + 1.0);
///
/// Gets the median of the distribution.
///
/// Throws .
public double Median => throw new NotSupportedException();
///
/// Gets the minimum of the distribution.
///
public double Minimum => 0.0;
///
/// Gets the maximum of the distribution.
///
public double Maximum => double.PositiveInfinity;
///
/// Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
///
/// The location at which to compute the density.
/// the density at .
///
public double Density(double x)
{
return x < 0.0 ? 0.0 : Math.Pow(_scale, _shape)*Math.Pow(x, -_shape - 1.0)*Math.Exp(-_scale/x)/SpecialFunctions.Gamma(_shape);
}
///
/// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
///
/// The location at which to compute the log density.
/// the log density at .
///
public double DensityLn(double x)
{
return Math.Log(Density(x));
}
///
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
///
/// The location at which to compute the cumulative distribution function.
/// the cumulative distribution at location .
///
public double CumulativeDistribution(double x)
{
return SpecialFunctions.GammaUpperRegularized(_shape, _scale/x);
}
///
/// Draws a random sample from the distribution.
///
/// A random number from this distribution.
public double Sample()
{
return SampleUnchecked(_random, _shape, _scale);
}
///
/// Fills an array with samples generated from the distribution.
///
public void Samples(double[] values)
{
SamplesUnchecked(_random, values, _shape, _scale);
}
///
/// Generates a sequence of samples from the Cauchy distribution.
///
/// a sequence of samples from the distribution.
public IEnumerable Samples()
{
return SamplesUnchecked(_random, _shape, _scale);
}
static double SampleUnchecked(System.Random rnd, double shape, double scale)
{
return 1.0/Gamma.SampleUnchecked(rnd, shape, scale);
}
static void SamplesUnchecked(System.Random rnd, double[] values, double shape, double scale)
{
Gamma.SamplesUnchecked(rnd, values, shape, scale);
CommonParallel.For(0, values.Length, 4096, (a, b) =>
{
for (int i = a; i < b; i++)
{
values[i] = 1.0/values[i];
}
});
}
static IEnumerable SamplesUnchecked(System.Random rnd, double shape, double scale)
{
return Gamma.SamplesUnchecked(rnd, shape, scale).Select(z => 1.0/z);
}
///
/// Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
///
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// The location at which to compute the density.
/// the density at .
///
public static double PDF(double shape, double scale, double x)
{
if (shape <= 0.0 || scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return x < 0.0 ? 0.0 : Math.Pow(scale, shape)*Math.Pow(x, -shape - 1.0)*Math.Exp(-scale/x)/SpecialFunctions.Gamma(shape);
}
///
/// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
///
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// The location at which to compute the density.
/// the log density at .
///
public static double PDFLn(double shape, double scale, double x)
{
return Math.Log(PDF(shape, scale, x));
}
///
/// Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
///
/// The location at which to compute the cumulative distribution function.
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// the cumulative distribution at location .
///
public static double CDF(double shape, double scale, double x)
{
if (shape <= 0.0 || scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SpecialFunctions.GammaUpperRegularized(shape, scale/x);
}
///
/// Generates a sample from the distribution.
///
/// The random number generator to use.
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// a sample from the distribution.
public static double Sample(System.Random rnd, double shape, double scale)
{
if (shape <= 0.0 || scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SampleUnchecked(rnd, shape, scale);
}
///
/// Generates a sequence of samples from the distribution.
///
/// The random number generator to use.
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// a sequence of samples from the distribution.
public static IEnumerable Samples(System.Random rnd, double shape, double scale)
{
if (shape <= 0.0 || scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SamplesUnchecked(rnd, shape, scale);
}
///
/// Fills an array with samples generated from the distribution.
///
/// The random number generator to use.
/// The array to fill with the samples.
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// a sequence of samples from the distribution.
public static void Samples(System.Random rnd, double[] values, double shape, double scale)
{
if (shape <= 0.0 || scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
SamplesUnchecked(rnd, values, shape, scale);
}
///
/// Generates a sample from the distribution.
///
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// a sample from the distribution.
public static double Sample(double shape, double scale)
{
if (shape <= 0.0 || scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SampleUnchecked(SystemRandomSource.Default, shape, scale);
}
///
/// Generates a sequence of samples from the distribution.
///
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// a sequence of samples from the distribution.
public static IEnumerable Samples(double shape, double scale)
{
if (shape <= 0.0 || scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SamplesUnchecked(SystemRandomSource.Default, shape, scale);
}
///
/// Fills an array with samples generated from the distribution.
///
/// The array to fill with the samples.
/// The shape (α) of the distribution. Range: α > 0.
/// The scale (β) of the distribution. Range: β > 0.
/// a sequence of samples from the distribution.
public static void Samples(double[] values, double shape, double scale)
{
if (shape <= 0.0 || scale <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
SamplesUnchecked(SystemRandomSource.Default, values, shape, scale);
}
}
}