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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 Pareto distribution.
/// The Pareto distribution is a power law probability distribution that coincides with social,
/// scientific, geophysical, actuarial, and many other types of observable phenomena.
/// For details about this distribution, see
/// Wikipedia - Pareto distribution.
///
public class Pareto : IContinuousDistribution
{
System.Random _random;
readonly double _scale;
readonly double _shape;
///
/// Initializes a new instance of the class.
///
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// If or are negative.
public Pareto(double scale, double shape)
{
if (!IsValidParameterSet(scale, shape))
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
_random = SystemRandomSource.Default;
_scale = scale;
_shape = shape;
}
///
/// Initializes a new instance of the class.
///
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// The random number generator which is used to draw random samples.
/// If or are negative.
public Pareto(double scale, double shape, System.Random randomSource)
{
if (!IsValidParameterSet(scale, shape))
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
_random = randomSource ?? SystemRandomSource.Default;
_scale = scale;
_shape = shape;
}
///
/// A string representation of the distribution.
///
/// a string representation of the distribution.
public override string ToString()
{
return $"Pareto(xm = {_scale}, α = {_shape})";
}
///
/// Tests whether the provided values are valid parameters for this distribution.
///
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
public static bool IsValidParameterSet(double scale, double shape)
{
return scale > 0.0 && shape > 0.0;
}
///
/// Gets the scale (xm) of the distribution. Range: xm > 0.
///
public double Scale => _scale;
///
/// Gets the shape (α) of the distribution. Range: α > 0.
///
public double Shape => _shape;
///
/// 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 _shape*_scale/(_shape - 1.0);
}
}
///
/// Gets the variance of the distribution.
///
public double Variance
{
get
{
if (_shape <= 2.0)
{
return double.PositiveInfinity;
}
return _scale*_scale*_shape/((_shape - 1.0)*(_shape - 1.0)*(_shape - 2.0));
}
}
///
/// Gets the standard deviation of the distribution.
///
public double StdDev => (_scale*Math.Sqrt(_shape))/(Math.Abs(_shape - 1.0)*Math.Sqrt(_shape - 2.0));
///
/// Gets the entropy of the distribution.
///
public double Entropy => Math.Log(_shape/_scale) - (1.0/_shape) - 1.0;
///
/// Gets the skewness of the distribution.
///
public double Skewness => (2.0*(_shape + 1.0)/(_shape - 3.0))*Math.Sqrt((_shape - 2.0)/_shape);
///
/// Gets the mode of the distribution.
///
public double Mode => _scale;
///
/// Gets the median of the distribution.
///
public double Median => _scale*Math.Pow(2.0, 1.0/_shape);
///
/// Gets the minimum of the distribution.
///
public double Minimum => _scale;
///
/// 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 _shape*Math.Pow(_scale, _shape)/Math.Pow(x, _shape + 1.0);
}
///
/// 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(_shape) + _shape*Math.Log(_scale) - (_shape + 1.0)*Math.Log(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 1.0 - Math.Pow(_scale/x, _shape);
}
///
/// Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
/// at the given probability. This is also known as the quantile or percent point function.
///
/// The location at which to compute the inverse cumulative density.
/// the inverse cumulative density at .
///
public double InverseCumulativeDistribution(double p)
{
return _scale*Math.Pow(1.0 - p, -1.0/_shape);
}
///
/// Draws a random sample from the distribution.
///
/// A random number from this distribution.
public double Sample()
{
return SampleUnchecked(_random, _scale, _shape);
}
///
/// Fills an array with samples generated from the distribution.
///
public void Samples(double[] values)
{
SamplesUnchecked(_random, values, _scale, _shape);
}
///
/// Generates a sequence of samples from the Pareto distribution.
///
/// a sequence of samples from the distribution.
public IEnumerable Samples()
{
return SamplesUnchecked(_random, _scale, _shape);
}
static double SampleUnchecked(System.Random rnd, double scale, double shape)
{
return scale*Math.Pow(rnd.NextDouble(), -1.0/shape);
}
static IEnumerable SamplesUnchecked(System.Random rnd, double scale, double shape)
{
var power = -1.0/shape;
return rnd.NextDoubleSequence().Select(x => scale*Math.Pow(x, power));
}
static void SamplesUnchecked(System.Random rnd, double[] values, double scale, double shape)
{
var power = -1.0/shape;
rnd.NextDoubles(values);
CommonParallel.For(0, values.Length, 4096, (a, b) =>
{
for (int i = a; i < b; i++)
{
values[i] = scale*Math.Pow(values[i], power);
}
});
}
///
/// Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
///
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// The location at which to compute the density.
/// the density at .
///
public static double PDF(double scale, double shape, double x)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return shape*Math.Pow(scale, shape)/Math.Pow(x, shape + 1.0);
}
///
/// Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
///
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// The location at which to compute the density.
/// the log density at .
///
public static double PDFLn(double scale, double shape, double x)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return Math.Log(shape) + shape*Math.Log(scale) - (shape + 1.0)*Math.Log(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 scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// the cumulative distribution at location .
///
public static double CDF(double scale, double shape, double x)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return 1.0 - Math.Pow(scale/x, shape);
}
///
/// Computes the inverse of the cumulative distribution function (InvCDF) for the distribution
/// at the given probability. This is also known as the quantile or percent point function.
///
/// The location at which to compute the inverse cumulative density.
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// the inverse cumulative density at .
///
public static double InvCDF(double scale, double shape, double p)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return scale*Math.Pow(1.0 - p, -1.0/shape);
}
///
/// Generates a sample from the distribution.
///
/// The random number generator to use.
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// a sample from the distribution.
public static double Sample(System.Random rnd, double scale, double shape)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return scale*Math.Pow(rnd.NextDouble(), -1.0/shape);
}
///
/// Generates a sequence of samples from the distribution.
///
/// The random number generator to use.
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// a sequence of samples from the distribution.
public static IEnumerable Samples(System.Random rnd, double scale, double shape)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SamplesUnchecked(rnd, scale, shape);
}
///
/// Fills an array with samples generated from the distribution.
///
/// The random number generator to use.
/// The array to fill with the samples.
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// a sequence of samples from the distribution.
public static void Samples(System.Random rnd, double[] values, double scale, double shape)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
SamplesUnchecked(rnd, values, scale, shape);
}
///
/// Generates a sample from the distribution.
///
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// a sample from the distribution.
public static double Sample(double scale, double shape)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SampleUnchecked(SystemRandomSource.Default, scale, shape);
}
///
/// Generates a sequence of samples from the distribution.
///
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// a sequence of samples from the distribution.
public static IEnumerable Samples(double scale, double shape)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
return SamplesUnchecked(SystemRandomSource.Default, scale, shape);
}
///
/// Fills an array with samples generated from the distribution.
///
/// The array to fill with the samples.
/// The scale (xm) of the distribution. Range: xm > 0.
/// The shape (α) of the distribution. Range: α > 0.
/// a sequence of samples from the distribution.
public static void Samples(double[] values, double scale, double shape)
{
if (scale <= 0.0 || shape <= 0.0)
{
throw new ArgumentException("Invalid parametrization for the distribution.");
}
SamplesUnchecked(SystemRandomSource.Default, values, scale, shape);
}
}
}