// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics // // Copyright (c) 2009-2013 Math.NET // // Permission is hereby granted, free of charge, to any person // obtaining a copy of this software and associated documentation // files (the "Software"), to deal in the Software without // restriction, including without limitation the rights to use, // copy, modify, merge, publish, distribute, sublicense, and/or sell // copies of the Software, and to permit persons to whom the // Software is furnished to do so, subject to the following // conditions: // // The above copyright notice and this permission notice shall be // included in all copies or substantial portions of the Software. // // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, // EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES // OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND // NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT // HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, // WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING // FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR // OTHER DEALINGS IN THE SOFTWARE. // 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); } } }