// // Math.NET Numerics, part of the Math.NET Project // http://numerics.mathdotnet.com // http://github.com/mathnet/mathnet-numerics // // Copyright (c) 2009-2014 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 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); } } }