jvangael
17 years ago
committed by
Christoph Ruegg
Christoph Ruegg
12 changed files with 1733 additions and 40 deletions
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// <copyright file="GammaTests.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://mathnet.opensourcedotnet.info
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//
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// Copyright (c) 2009 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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namespace MathNet.Numerics.UnitTests.DistributionTests |
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{ |
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using System; |
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using System.Linq; |
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using MbUnit.Framework; |
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using MathNet.Numerics.Distributions; |
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[TestFixture] |
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public class CommonDistributionTests |
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{ |
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private IDistribution[] dists; |
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[SetUp] |
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public void SetupDistributions() |
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{ |
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dists = new IDistribution[4]; |
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dists[0] = new Beta(1.0, 1.0); |
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dists[1] = new ContinuousUniform(0.0, 1.0); |
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dists[2] = new Gamma(1.0, 1.0); |
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dists[3] = new Normal(0.0, 1.0); |
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} |
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[Test] |
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[Row(0)] |
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[Row(1)] |
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[Row(2)] |
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[Row(3)] |
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public void CanCreateNormal(int i) |
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{ |
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Assert.IsNotNull(dists[i].RandomSource); |
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} |
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[Test] |
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[Row(0)] |
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[Row(1)] |
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[Row(2)] |
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[Row(3)] |
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public void CanSetRandomSource(int i) |
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{ |
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dists[i].RandomSource = new Random(); |
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} |
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[Test] |
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[Row(0)] |
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[Row(1)] |
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[Row(2)] |
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[Row(3)] |
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[ExpectedException(typeof(ArgumentNullException))] |
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public void FailSetRandomSourceWithNullReference(int i) |
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{ |
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dists[i].RandomSource = null; |
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} |
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} |
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} |
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// <copyright file="BetaTests.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://mathnet.opensourcedotnet.info
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//
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// Copyright (c) 2009 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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|
// obtaining a copy of this software and associated documentation
|
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|
// files (the "Software"), to deal in the Software without
|
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|
// restriction, including without limitation the rights to use,
|
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|
// copy, modify, merge, publish, distribute, sublicense, and/or sell
|
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|
// copies of the Software, and to permit persons to whom the
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|
// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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|
// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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|
// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
|
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|
// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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|
// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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namespace MathNet.Numerics.UnitTests.DistributionTests |
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{ |
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using System; |
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using System.Linq; |
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using MbUnit.Framework; |
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using MathNet.Numerics.Distributions; |
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[TestFixture] |
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public class BetaTests |
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{ |
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[SetUp] |
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public void SetUp() |
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{ |
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Control.CheckDistributionParameters = true; |
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} |
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[Test, MultipleAsserts] |
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[Row(0.0, 0.0)] |
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[Row(0.0, 0.1)] |
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[Row(1.0, 0.0)] |
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[Row(1.0, 1.0)] |
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[Row(9.0, 1.0)] |
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[Row(5.0, 100.0)] |
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[Row(1.0, Double.PositiveInfinity)] |
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[Row(Double.PositiveInfinity, 1.0)] |
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[Row(0.0, Double.PositiveInfinity)] |
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[Row(Double.PositiveInfinity, 0.0)] |
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public void CanCreateBeta(double a, double b) |
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{ |
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var n = new Beta(a, b); |
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AssertEx.AreEqual<double>(a, n.A); |
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AssertEx.AreEqual<double>(b, n.B); |
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} |
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[Test] |
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[ExpectedException(typeof(ArgumentOutOfRangeException))] |
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[Row(Double.NaN, 1.0)] |
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[Row(1.0, Double.NaN)] |
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[Row(Double.NaN, Double.NaN)] |
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[Row(1.0, -1.0)] |
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[Row(-1.0, 1.0)] |
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[Row(-1.0, -1.0)] |
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public void BetaCreateFailsWithBadParameters(double a, double b) |
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{ |
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var n = new Beta(a, b); |
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} |
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[Test] |
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public void ValidateToString() |
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{ |
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var n = new Beta(1.0, 2.0); |
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AssertEx.AreEqual<string>("Beta(A = 1, B = 2)", n.ToString()); |
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} |
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[Test] |
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[Row(-0.0)] |
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[Row(0.0)] |
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[Row(0.1)] |
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[Row(1.0)] |
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[Row(10.0)] |
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[Row(Double.PositiveInfinity)] |
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public void CanSetShapeA(double a) |
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{ |
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var n = new Beta(1.0, 1.0); |
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n.A = a; |
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} |
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[Test] |
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[ExpectedException(typeof(ArgumentOutOfRangeException))] |
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public void SetShapeAFailsWithNegativeA() |
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{ |
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var n = new Beta(1.0, 1.0); |
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n.A = -1.0; |
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} |
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[Test] |
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[Row(-0.0)] |
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[Row(0.0)] |
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[Row(0.1)] |
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[Row(1.0)] |
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[Row(10.0)] |
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[Row(Double.PositiveInfinity)] |
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public void CanSetShapeB(double b) |
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{ |
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var n = new Beta(1.0, 1.0); |
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n.B = b; |
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} |
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[Test] |
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[ExpectedException(typeof(ArgumentOutOfRangeException))] |
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public void SetShapeBFailsWithNegativeB() |
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{ |
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var n = new Beta(1.0, 1.0); |
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n.B = -1.0; |
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} |
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[Test] |
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[Row(0.0, 0.0, 0.5)] |
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[Row(0.0, 0.1, 0.1)] |
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[Row(1.0, 0.0, 1.0)] |
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[Row(1.0, 1.0, 0.5)] |
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[Row(9.0, 1.0, 0.9)] |
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[Row(5.0, 100.0, 0.047619047619047619047616)] |
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[Row(1.0, Double.PositiveInfinity, 1.0)] |
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[Row(Double.PositiveInfinity, 1.0, 0.0)] |
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[Row(0.0, Double.PositiveInfinity, 1.0)] |
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[Row(Double.PositiveInfinity, 0.0, 0.0)] |
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public void ValidateMean(double a, double b, double mean) |
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{ |
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var n = new Beta(a, b); |
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AssertEx.AreEqual<double>(mean, n.Mean); |
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} |
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[Test] |
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[Row(0.0, 0.0, 0.5)] |
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[Row(0.0, 0.1, 0.1)] |
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[Row(1.0, 0.0, 1.0)] |
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[Row(1.0, 1.0, 0.0)] |
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[Row(9.0, 1.0, -1.3083356884473304939016015849561625204060922267565917)] |
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[Row(5.0, 100.0, -2.5201623187602743679459255108827601222133603091753153)] |
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[Row(1.0, Double.PositiveInfinity, 0.0)] |
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[Row(Double.PositiveInfinity, 1.0, 0.0)] |
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[Row(0.0, Double.PositiveInfinity, 0.0)] |
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[Row(Double.PositiveInfinity, 0.0, 0.0)] |
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public void ValidateEntropy(double a, double b, double entropy) |
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{ |
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var n = new Beta(a, b); |
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AssertEx.AreEqual<double>(entropy, n.Entropy); |
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} |
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[Test] |
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[Row(0.0, 0.0, 0.0)] |
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[Row(0.0, 0.1, 2.0)] |
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[Row(1.0, 0.0, -2.0)] |
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[Row(1.0, 1.0, 0.0)] |
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[Row(9.0, 1.0, -1.4740554623801777107177478829647496373009282424841579)] |
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[Row(5.0, 100.0, 0.81759410927553430354583159143895018978562196953345572)] |
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[Row(1.0, Double.PositiveInfinity, 2.0)] |
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[Row(Double.PositiveInfinity, 1.0, -2.0)] |
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[Row(0.0, Double.PositiveInfinity, 2.0)] |
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[Row(Double.PositiveInfinity, 0.0, -2.0)] |
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public void ValidateSkewness(double a, double b, double skewness) |
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{ |
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var n = new Beta(a, b); |
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AssertEx.AreEqual<double>(skewness, n.Skewness); |
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} |
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[Test] |
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[Row(0.0, 0.0, 0.5)] |
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[Row(0.0, 0.1, 1.0)] |
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[Row(1.0, 0.0, 0.0)] |
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[Row(1.0, 1.0, 0.5)] |
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[Row(9.0, 1.0, 1.0)] |
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[Row(5.0, 100.0, 0.038834951456310676243255386452801758423447608947753906)] |
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[Row(1.0, Double.PositiveInfinity, 0.0)] |
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[Row(Double.PositiveInfinity, 1.0, 1.0)] |
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[Row(0.0, Double.PositiveInfinity, 0.0)] |
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[Row(Double.PositiveInfinity, 0.0, 1.0)] |
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public void ValidateMode(double a, double b, double mode) |
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{ |
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var n = new Beta(a, b); |
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AssertEx.AreEqual<double>(mode, n.Mode); |
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} |
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[Test] |
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[ExpectedException(typeof(NotSupportedException))] |
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[Row(0.0, 0.0)] |
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[Row(0.0, 0.1)] |
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[Row(1.0, 0.0)] |
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[Row(1.0, 1.0)] |
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[Row(9.0, 1.0)] |
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[Row(5.0, 100.0)] |
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[Row(1.0, Double.PositiveInfinity)] |
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[Row(Double.PositiveInfinity, 1.0)] |
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[Row(0.0, Double.PositiveInfinity)] |
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[Row(Double.PositiveInfinity, 0.0)] |
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public void ValidateMedian(double a, double b) |
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{ |
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var n = new Beta(a, 1.0); |
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var m = n.Median; |
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} |
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[Test] |
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public void ValidateMinimum() |
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{ |
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var n = new Beta(1.0, 1.0); |
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AssertEx.AreEqual<double>(0.0, n.Minimum); |
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} |
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[Test] |
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public void ValidateMaximum() |
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{ |
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var n = new Beta(1.0, 1.0); |
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AssertEx.AreEqual<double>(1.0, n.Maximum); |
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} |
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[Test] |
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public void CanSampleStatic() |
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{ |
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var d = Beta.Sample(new Random(), 2.0, 3.0); |
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} |
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[Test] |
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public void CanSampleSequenceStatic() |
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{ |
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var ied = Beta.Samples(new Random(), 2.0, 3.0); |
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var arr = ied.Take(5).ToArray(); |
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} |
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[Test] |
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[ExpectedException(typeof(ArgumentOutOfRangeException))] |
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public void FailSampleStatic() |
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{ |
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var d = Beta.Sample(new Random(), 1.0, -1.0); |
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} |
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[Test] |
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[ExpectedException(typeof(ArgumentOutOfRangeException))] |
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public void FailSampleSequenceStatic() |
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{ |
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var ied = Beta.Samples(new Random(), 1.0, -1.0).First(); |
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} |
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[Test] |
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public void CanSample() |
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{ |
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var n = new Beta(2.0, 3.0); |
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var d = n.Sample(); |
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} |
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[Test] |
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public void CanSampleSequence() |
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{ |
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var n = new Beta(2.0, 3.0); |
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var ied = n.Samples(); |
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var e = ied.Take(5).ToArray(); |
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} |
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[Test] |
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[Row(0.0, 0.0, 0.0, Double.PositiveInfinity)] |
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[Row(0.0, 0.0, 0.5, 0.0)] |
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[Row(0.0, 0.0, 1.0, Double.PositiveInfinity)] |
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[Row(0.0, 0.1, 0.0, Double.PositiveInfinity)] |
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[Row(0.0, 0.1, 0.5, 0.0)] |
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[Row(0.0, 0.1, 1.0, 0.0)] |
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[Row(1.0, 0.0, 0.0, 0.0)] |
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[Row(1.0, 0.0, 0.5, 0.0)] |
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[Row(1.0, 0.0, 1.0, Double.PositiveInfinity)] |
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[Row(1.0, 1.0, 0.0, 1.0)] |
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[Row(1.0, 1.0, 0.5, 1.0)] |
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[Row(1.0, 1.0, 1.0, 1.0)] |
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[Row(9.0, 1.0, 0.0, 0.0)] |
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[Row(9.0, 1.0, 0.5, 0.035155378090821160189479427593561667617370600927556366)] |
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[Row(9.0, 1.0, 1.0, 8.9997767912502170085067334639517869100468738374544298)] |
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[Row(5.0, 100.0, 0.0, 0.0)] |
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[Row(5.0, 100.0, 0.5, 1.0881845516040810386311829462908430145307026037926335e-21)] |
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[Row(5.0, 100.0, 1.0, 0.0)] |
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[Row(1.0, Double.PositiveInfinity, 0.0, Double.PositiveInfinity)] |
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[Row(1.0, Double.PositiveInfinity, 0.5, 0.0)] |
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[Row(1.0, Double.PositiveInfinity, 1.0, 0.0)] |
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[Row(Double.PositiveInfinity, 1.0, 0.0, 0.0)] |
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[Row(Double.PositiveInfinity, 1.0, 0.5, 0.0)] |
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[Row(Double.PositiveInfinity, 1.0, 1.0, Double.PositiveInfinity)] |
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[Row(0.0, Double.PositiveInfinity, 0.0, Double.PositiveInfinity)] |
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[Row(0.0, Double.PositiveInfinity, 0.5, 0.0)] |
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[Row(0.0, Double.PositiveInfinity, 1.0, 0.0)] |
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[Row(Double.PositiveInfinity, 0.0, 0.0, 0.0)] |
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[Row(Double.PositiveInfinity, 0.0, 0.5, 0.0)] |
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[Row(Double.PositiveInfinity, 0.0, 1.0, Double.PositiveInfinity)] |
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public void ValidateDensity(double a, double b, double x, double pdf) |
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{ |
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var n = new Beta(a, b); |
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AssertHelpers.AlmostEqual(pdf, n.Density(x), 15); |
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} |
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[Test] |
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[Row(0.0, 0.0, 0.0, Double.PositiveInfinity)] |
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[Row(0.0, 0.0, 0.5, Double.NegativeInfinity)] |
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[Row(0.0, 0.0, 1.0, Double.PositiveInfinity)] |
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[Row(0.0, 0.1, 0.0, Double.PositiveInfinity)] |
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[Row(0.0, 0.1, 0.5, Double.NegativeInfinity)] |
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[Row(0.0, 0.1, 1.0, Double.NegativeInfinity)] |
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[Row(1.0, 0.0, 0.0, Double.NegativeInfinity)] |
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[Row(1.0, 0.0, 0.5, Double.NegativeInfinity)] |
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[Row(1.0, 0.0, 1.0, Double.PositiveInfinity)] |
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[Row(1.0, 1.0, 0.0, 0.0)] |
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[Row(1.0, 1.0, 0.5, 0.0)] |
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[Row(1.0, 1.0, 1.0, 0.0)] |
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[Row(9.0, 1.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(9.0, 1.0, 0.5, -3.3479528671433430925473664978203611353090199592365404)] |
||||
|
[Row(9.0, 1.0, 1.0, 2.197199776056471990627201569939718235188380979206923)] |
||||
|
[Row(5.0, 100.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(5.0, 100.0, 0.5, -51.447830024537682154565870837960406410586196074573801)] |
||||
|
[Row(5.0, 100.0, 1.0, Double.NegativeInfinity)] |
||||
|
[Row(1.0, Double.PositiveInfinity, 0.0, Double.PositiveInfinity)] |
||||
|
[Row(1.0, Double.PositiveInfinity, 0.5, Double.NegativeInfinity)] |
||||
|
[Row(1.0, Double.PositiveInfinity, 1.0, Double.NegativeInfinity)] |
||||
|
[Row(Double.PositiveInfinity, 1.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(Double.PositiveInfinity, 1.0, 0.5, Double.NegativeInfinity)] |
||||
|
[Row(Double.PositiveInfinity, 1.0, 1.0, Double.PositiveInfinity)] |
||||
|
[Row(0.0, Double.PositiveInfinity, 0.0, Double.PositiveInfinity)] |
||||
|
[Row(0.0, Double.PositiveInfinity, 0.5, Double.NegativeInfinity)] |
||||
|
[Row(0.0, Double.PositiveInfinity, 1.0, Double.NegativeInfinity)] |
||||
|
[Row(Double.PositiveInfinity, 0.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(Double.PositiveInfinity, 0.0, 0.5, Double.NegativeInfinity)] |
||||
|
[Row(Double.PositiveInfinity, 0.0, 1.0, Double.PositiveInfinity)] |
||||
|
public void ValidateDensityLn(double a, double b, double x, double pdfln) |
||||
|
{ |
||||
|
var n = new Beta(a, b); |
||||
|
AssertHelpers.AlmostEqual(pdfln, n.DensityLn(x), 15); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, 0.0, 0.5)] |
||||
|
[Row(0.0, 0.0, 0.5, 0.5)] |
||||
|
[Row(0.0, 0.0, 1.0, 1.0)] |
||||
|
[Row(0.0, 0.1, 0.0, 1.0)] |
||||
|
[Row(0.0, 0.1, 0.5, 1.0)] |
||||
|
[Row(0.0, 0.1, 1.0, 1.0)] |
||||
|
[Row(1.0, 0.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 0.0, 0.5, 0.0)] |
||||
|
[Row(1.0, 0.0, 1.0, 1.0)] |
||||
|
[Row(1.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 1.0, 0.5, 0.5)] |
||||
|
[Row(1.0, 1.0, 1.0, 1.0)] |
||||
|
[Row(9.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(9.0, 1.0, 0.5, 0.00195313)] |
||||
|
[Row(9.0, 1.0, 1.0, 1.0)] |
||||
|
[Row(5.0, 100.0, 0.0, 0.0)] |
||||
|
[Row(5.0, 100.0, 0.5, 1.0)] |
||||
|
[Row(5.0, 100.0, 1.0, 1.0)] |
||||
|
[Row(1.0, Double.PositiveInfinity, 0.0, 1.0)] |
||||
|
[Row(1.0, Double.PositiveInfinity, 0.5, 1.0)] |
||||
|
[Row(1.0, Double.PositiveInfinity, 1.0, 1.0)] |
||||
|
[Row(Double.PositiveInfinity, 1.0, 0.0, 0.0)] |
||||
|
[Row(Double.PositiveInfinity, 1.0, 0.5, 0.0)] |
||||
|
[Row(Double.PositiveInfinity, 1.0, 1.0, 1.0)] |
||||
|
[Row(0.0, Double.PositiveInfinity, 0.0, 1.0)] |
||||
|
[Row(0.0, Double.PositiveInfinity, 0.5, 1.0)] |
||||
|
[Row(0.0, Double.PositiveInfinity, 1.0, 1.0)] |
||||
|
[Row(Double.PositiveInfinity, 0.0, 0.0, 0.0)] |
||||
|
[Row(Double.PositiveInfinity, 0.0, 0.5, 0.0)] |
||||
|
[Row(Double.PositiveInfinity, 0.0, 1.0, 1.0)] |
||||
|
public void ValidateCumulativeDistribution(double a, double b, double x, double cdf) |
||||
|
{ |
||||
|
var n = new Beta(a, b); |
||||
|
AssertHelpers.AlmostEqual(cdf, n.CumulativeDistribution(x), 15); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
@ -0,0 +1,393 @@ |
|||||
|
// <copyright file="GammaTests.cs" company="Math.NET">
|
||||
|
// Math.NET Numerics, part of the Math.NET Project
|
||||
|
// http://mathnet.opensourcedotnet.info
|
||||
|
//
|
||||
|
// Copyright (c) 2009 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.
|
||||
|
// </copyright>
|
||||
|
|
||||
|
namespace MathNet.Numerics.UnitTests.DistributionTests |
||||
|
{ |
||||
|
using System; |
||||
|
using System.Linq; |
||||
|
using MbUnit.Framework; |
||||
|
using MathNet.Numerics.Distributions; |
||||
|
|
||||
|
[TestFixture] |
||||
|
public class GammaTests |
||||
|
{ |
||||
|
[SetUp] |
||||
|
public void SetUp() |
||||
|
{ |
||||
|
Control.CheckDistributionParameters = true; |
||||
|
} |
||||
|
|
||||
|
[Test, MultipleAsserts] |
||||
|
[Row(0.0, 0.0)] |
||||
|
[Row(1.0, 0.1)] |
||||
|
[Row(1.0, 1.0)] |
||||
|
[Row(10.0, 10.0)] |
||||
|
[Row(10.0, 1.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity)] |
||||
|
public void CanCreateGamma(double shape, double invScale) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertEx.AreEqual<double>(shape, n.Shape); |
||||
|
AssertEx.AreEqual<double>(invScale, n.InvScale); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
[Row(Double.NaN, 1.0)] |
||||
|
[Row(1.0, Double.NaN)] |
||||
|
[Row(Double.NaN, Double.NaN)] |
||||
|
[Row(1.0, -1.0)] |
||||
|
[Row(-1.0, 1.0)] |
||||
|
[Row(-1.0, -1.0)] |
||||
|
public void GammaCreateFailsWithBadParameters(double shape, double invScale) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
} |
||||
|
|
||||
|
[Test, MultipleAsserts] |
||||
|
[Row(0.0, 0.0)] |
||||
|
[Row(1.0, 0.1)] |
||||
|
[Row(1.0, 1.0)] |
||||
|
[Row(10.0, 10.0)] |
||||
|
[Row(10.0, 1.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity)] |
||||
|
public void CanCreateGammaWithShapeInvScale(double shape, double invScale) |
||||
|
{ |
||||
|
var n = Gamma.WithShapeInvScale(shape, invScale); |
||||
|
AssertEx.AreEqual<double>(shape, n.Shape); |
||||
|
AssertEx.AreEqual<double>(invScale, n.InvScale); |
||||
|
} |
||||
|
|
||||
|
[Test, MultipleAsserts] |
||||
|
[Row(0.0, 0.0)] |
||||
|
[Row(1.0, 0.1)] |
||||
|
[Row(1.0, 1.0)] |
||||
|
[Row(10.0, 10.0)] |
||||
|
[Row(10.0, 1.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity)] |
||||
|
public void CanCreateGammaWithShapeScale(double shape, double scale) |
||||
|
{ |
||||
|
var n = Gamma.WithShapeScale(shape, scale); |
||||
|
AssertEx.AreEqual<double>(shape, n.Shape); |
||||
|
AssertEx.AreEqual<double>(scale, n.Scale); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void ValidateToString() |
||||
|
{ |
||||
|
var n = new Gamma(1.0, 2.0); |
||||
|
AssertEx.AreEqual<string>("Gamma(Shape = 1, Inverse Scale = 2)", n.ToString()); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(-0.0)] |
||||
|
[Row(0.0)] |
||||
|
[Row(0.1)] |
||||
|
[Row(1.0)] |
||||
|
[Row(10.0)] |
||||
|
[Row(Double.PositiveInfinity)] |
||||
|
public void CanSetShape(double shape) |
||||
|
{ |
||||
|
var n = new Gamma(1.0, 1.0); |
||||
|
n.Shape = shape; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
public void SetShapeFailsWithNegativeShape() |
||||
|
{ |
||||
|
var n = new Gamma(1.0, 1.0); |
||||
|
n.Shape = -1.0; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(-0.0)] |
||||
|
[Row(0.0)] |
||||
|
[Row(0.1)] |
||||
|
[Row(1.0)] |
||||
|
[Row(10.0)] |
||||
|
[Row(Double.PositiveInfinity)] |
||||
|
public void CanSetScale(double scale) |
||||
|
{ |
||||
|
var n = new Gamma(1.0, 1.0); |
||||
|
n.Scale = scale; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
public void SetScaleFailsWithNegativeScale() |
||||
|
{ |
||||
|
var n = new Gamma(1.0, 1.0); |
||||
|
n.Scale = -1.0; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(-0.0)] |
||||
|
[Row(0.0)] |
||||
|
[Row(0.1)] |
||||
|
[Row(1.0)] |
||||
|
[Row(10.0)] |
||||
|
[Row(Double.PositiveInfinity)] |
||||
|
public void CanSetInvScale(double invScale) |
||||
|
{ |
||||
|
var n = new Gamma(1.0, 1.0); |
||||
|
n.InvScale = invScale; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
public void SetInvScaleFailsWithNegativeInvScale() |
||||
|
{ |
||||
|
var n = new Gamma(1.0, 1.0); |
||||
|
n.InvScale = -1.0; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 0.1, 10.0)] |
||||
|
[Row(1.0, 1.0, 1.0)] |
||||
|
[Row(10.0, 10.0, 1.0)] |
||||
|
[Row(10.0, 1.0, 10.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 0.0)] |
||||
|
public void CanGetMean(double shape, double invScale, double mean) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertEx.AreEqual<double>(mean, n.Mean); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 0.1, 100.0)] |
||||
|
[Row(1.0, 1.0, 1.0)] |
||||
|
[Row(10.0, 10.0, 0.1)] |
||||
|
[Row(10.0, 1.0, 10.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 0.0)] |
||||
|
public void CanGetVariance(double shape, double invScale, double var) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertEx.AreEqual<double>(var, n.Variance); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 0.1, 10.0)] |
||||
|
[Row(1.0, 1.0, 1.0)] |
||||
|
[Row(10.0, 10.0, 0.31622776601683794197697302588502426416723164097476643)] |
||||
|
[Row(10.0, 1.0, 3.1622776601683793319988935444327185337195551393252168)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 0.0)] |
||||
|
public void CanGetStdDev(double shape, double invScale, double sdev) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertHelpers.AlmostEqual(sdev, n.StdDev, 15); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, Double.PositiveInfinity)] |
||||
|
[Row(1.0, 0.1, 3.3025850929940456285068402234265387271634735938763824)] |
||||
|
[Row(1.0, 1.0, 1.0)] |
||||
|
[Row(10.0, 10.0, 0.23346908548693395836262094490967812177376750477943892)] |
||||
|
[Row(10.0, 1.0, 2.5360541784809796423806123995940423293748689934081866)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 0.0)] |
||||
|
public void ValidateEntropy(double shape, double invScale, double entropy) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertHelpers.AlmostEqual(entropy, n.Entropy, 15); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, Double.PositiveInfinity)] |
||||
|
[Row(1.0, 0.1, 2.0)] |
||||
|
[Row(1.0, 1.0, 2.0)] |
||||
|
[Row(10.0, 10.0, 0.63245553203367586639977870888654370674391102786504337)] |
||||
|
[Row(10.0, 1.0, 0.63245553203367586639977870888654370674391102786504337)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 0.0)] |
||||
|
public void ValidateSkewness(double shape, double invScale, double skewness) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertHelpers.AlmostEqual(skewness, n.Skewness, 15); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, Double.PositiveInfinity)] |
||||
|
[Row(1.0, 0.1, 0.0)] |
||||
|
[Row(1.0, 1.0, 0.0)] |
||||
|
[Row(10.0, 10.0, 0.9)] |
||||
|
[Row(10.0, 1.0, 9.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 10.0)] |
||||
|
public void ValidateMode(double shape, double invScale, double mode) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertEx.AreEqual<double>(mode, n.Mode); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(NotSupportedException))] |
||||
|
[Row(0.0, 0.0)] |
||||
|
[Row(1.0, 0.1)] |
||||
|
[Row(1.0, 1.0)] |
||||
|
[Row(10.0, 10.0)] |
||||
|
[Row(10.0, 1.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity)] |
||||
|
public void ValidateMedian(double shape, double invScale, double mode) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
var median = n.Median; |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void ValidateMinimum() |
||||
|
{ |
||||
|
var n = new Gamma(1.0,1.0); |
||||
|
AssertEx.AreEqual<double>(0.0, n.Minimum); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void ValidateMaximum() |
||||
|
{ |
||||
|
var n = new Gamma(1.0, 1.0); |
||||
|
AssertEx.AreEqual<double>(System.Double.PositiveInfinity, n.Maximum); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, 0.0, 0.0)] |
||||
|
[Row(0.0, 0.0, 1.0, 0.0)] |
||||
|
[Row(0.0, 0.0, 10.0, 0.0)] |
||||
|
[Row(1.0, 0.1, 0.0, 0.10000000000000000555111512312578270211815834045410156)] |
||||
|
[Row(1.0, 0.1, 1.0, 0.099004983374916810660915381324116279472953858297127391)] |
||||
|
[Row(1.0, 0.1, 10.0, 0.036787944117144234201693506390001264039984687455876246)] |
||||
|
[Row(1.0, 1.0, 0.0, 1.0)] |
||||
|
[Row(1.0, 1.0, 1.0, 0.36787944117144232159552377016146086744581113103176804)] |
||||
|
[Row(1.0, 1.0, 10.0, 0.000045399929762484851535591515560550610237918088866564953)] |
||||
|
[Row(10.0, 10.0, 0.0, 0.0)] |
||||
|
[Row(10.0, 10.0, 1.0, 1.2511003572113329898476497894772544708420990097708588)] |
||||
|
[Row(10.0, 10.0, 10.0, 1.0251532120868705806216092933926141802686541811003037e-30)] |
||||
|
[Row(10.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(10.0, 1.0, 1.0, 0.0000010137771196302974029859010421116095333052555418644397)] |
||||
|
[Row(10.0, 1.0, 10.0, 0.12511003572113329898476497894772544708420990097708601)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 0.0, 0.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 1.0, 0.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 10.0, Double.PositiveInfinity)] |
||||
|
public void ValidateDensity(double shape, double invScale, double x, double pdf) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertHelpers.AlmostEqual(pdf, n.Density(x), 15); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(0.0, 0.0, 1.0, Double.NegativeInfinity)] |
||||
|
[Row(0.0, 0.0, 10.0, Double.NegativeInfinity)] |
||||
|
[Row(1.0, 0.1, 0.0, -2.3025850929940456285068402234265387271634735938763824)] |
||||
|
[Row(1.0, 0.1, 1.0, -2.312585092994045630449730516520562672904829013035318)] |
||||
|
[Row(1.0, 0.1, 10.0, -3.3025850929940456285068402234265387271634735938763824)] |
||||
|
[Row(1.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 1.0, 1.0, -1.0)] |
||||
|
[Row(1.0, 1.0, 10.0, -10.0)] |
||||
|
[Row(10.0, 10.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(10.0, 10.0, 1.0, 0.22402344985898722897219667227693591172986563062456522)] |
||||
|
[Row(10.0, 10.0, 10.0, -69.052710713194601614865880235563786219860220971716511)] |
||||
|
[Row(10.0, 1.0, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(10.0, 1.0, 1.0, -13.801827480081469611207717874566706164281149255663166)] |
||||
|
[Row(10.0, 1.0, 10.0, -2.0785616431350584550457947824074282958712358580042068)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 0.0, Double.NegativeInfinity)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 1.0, Double.NegativeInfinity)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 10.0, Double.PositiveInfinity)] |
||||
|
public void ValidateDensityLn(double shape, double invScale, double x, double pdfln) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertHelpers.AlmostEqual(pdfln, n.DensityLn(x), 15); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void CanSampleStatic() |
||||
|
{ |
||||
|
var d = Gamma.Sample(new Random(), 1.0, 1.0); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void CanSampleSequenceStatic() |
||||
|
{ |
||||
|
var ied = Gamma.Samples(new Random(), 1.0, 1.0); |
||||
|
var arr = ied.Take(5).ToArray(); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
public void FailSampleStatic() |
||||
|
{ |
||||
|
var d = Normal.Sample(new Random(), 1.0, -1.0); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[ExpectedException(typeof(ArgumentOutOfRangeException))] |
||||
|
public void FailSampleSequenceStatic() |
||||
|
{ |
||||
|
var ied = Normal.Samples(new Random(), 1.0, -1.0).First(); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void CanSample() |
||||
|
{ |
||||
|
var n = new Normal(); |
||||
|
var d = n.Sample(); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
public void CanSampleSequence() |
||||
|
{ |
||||
|
var n = new Normal(); |
||||
|
var ied = n.Samples(); |
||||
|
var e = ied.Take(5).ToArray(); |
||||
|
} |
||||
|
|
||||
|
[Test] |
||||
|
[Row(0.0, 0.0, 0.0, 0.0)] |
||||
|
[Row(0.0, 0.0, 1.0, 0.0)] |
||||
|
[Row(0.0, 0.0, 10.0, 0.0)] |
||||
|
[Row(1.0, 0.1, 0.0, 0.0)] |
||||
|
[Row(1.0, 0.1, 1.0, 0.095162581964040431858607615783064404690935346242622848)] |
||||
|
[Row(1.0, 0.1, 10.0, 0.63212055882855767840447622983853913255418886896823196)] |
||||
|
[Row(1.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(1.0, 1.0, 1.0, 0.63212055882855767840447622983853913255418886896823196)] |
||||
|
[Row(1.0, 1.0, 10.0, 0.99995460007023751514846440848443944938976208191113396)] |
||||
|
[Row(10.0, 10.0, 0.0, 0.0)] |
||||
|
[Row(10.0, 10.0, 1.0, 0.54207028552814779168583514294066541824736464003242184)] |
||||
|
[Row(10.0, 10.0, 10.0, 0.99999999999999999999999999999988746526039157266114706)] |
||||
|
[Row(10.0, 1.0, 0.0, 0.0)] |
||||
|
[Row(10.0, 1.0, 1.0, 0.00000011142547833872067735305068724025236288094949815466035)] |
||||
|
[Row(10.0, 1.0, 10.0, 0.54207028552814779168583514294066541824736464003242184)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 0.0, 0.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 1.0, 0.0)] |
||||
|
[Row(10.0, Double.PositiveInfinity, 10.0, 1.0)] |
||||
|
public void ValidateCumulativeDistribution(double shape, double invScale, double x, double cdf) |
||||
|
{ |
||||
|
var n = new Gamma(shape, invScale); |
||||
|
AssertHelpers.AlmostEqual(cdf, n.CumulativeDistribution(x), 15); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
@ -0,0 +1,324 @@ |
|||||
|
// <copyright file="Beta.cs" company="Math.NET">
|
||||
|
// Math.NET Numerics, part of the Math.NET Project
|
||||
|
// http://mathnet.opensourcedotnet.info
|
||||
|
//
|
||||
|
// Copyright (c) 2009 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.
|
||||
|
// </copyright>
|
||||
|
|
||||
|
namespace MathNet.Numerics.Distributions |
||||
|
{ |
||||
|
using System; |
||||
|
using System.Collections.Generic; |
||||
|
using Properties; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Implements the Beta distribution. For details about this distribution, see
|
||||
|
/// <a href="http://en.wikipedia.org/wiki/Beta_distribution">Wikipedia - Beta distribution</a>.
|
||||
|
/// </summary>
|
||||
|
/// <remarks><para>The distribution will use the <see cref="System.Random"/> by default.
|
||||
|
/// Users can get/set the random number generator by using the <see cref="RandomSource"/> property.</para>
|
||||
|
/// <para>The statistics classes will check all the incoming parameters whether they are in the allowed
|
||||
|
/// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters
|
||||
|
/// to false, all parameter checks can be turned off.</para></remarks>
|
||||
|
public class Beta : IContinuousDistribution |
||||
|
{ |
||||
|
/// <summary>
|
||||
|
/// Beta shape parameter a.
|
||||
|
/// </summary>
|
||||
|
private double _shapeA; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Beta shape parameter b.
|
||||
|
/// </summary>
|
||||
|
private double _shapeB; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Initializes a new instance of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="a">The a shape parameter of the Beta distribution.</param>
|
||||
|
/// <param name="b">The b shape parameter of the Beta distribution.</param>
|
||||
|
/// <exception cref="ArgumentOutOfRangeException">If any of the Beta parameters are negative.</exception>
|
||||
|
public Beta(double a, double b) |
||||
|
{ |
||||
|
SetParameters(a, b); |
||||
|
RandomSource = new Random(); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// A string representation of the distribution.
|
||||
|
/// </summary>
|
||||
|
public override string ToString() |
||||
|
{ |
||||
|
return "Beta(A = " + _shapeA + ", B = " + _shapeB + ")"; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Checks whether the parameters of the distribution are valid.
|
||||
|
/// </summary>
|
||||
|
/// <param name="a">The a shape parameter of the Beta distribution.</param>
|
||||
|
/// <param name="b">The b shape parameter of the Beta distribution.</param>
|
||||
|
/// <returns>True when the parameters are valid, false otherwise.</returns>
|
||||
|
private static bool IsValidParameterSet(double a, double b) |
||||
|
{ |
||||
|
if (a < 0.0 || b < 0.0) |
||||
|
{ |
||||
|
return false; |
||||
|
} |
||||
|
|
||||
|
return true; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Sets the parameters of the distribution after checking their validity.
|
||||
|
/// </summary>
|
||||
|
/// <param name="a">The a shape parameter of the Beta distribution.</param>
|
||||
|
/// <param name="b">The b shape parameter of the Beta distribution.</param>
|
||||
|
/// <exception cref="ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
|
||||
|
private void SetParameters(double a, double b) |
||||
|
{ |
||||
|
if (Control.CheckDistributionParameters && !IsValidParameterSet(a, b)) |
||||
|
{ |
||||
|
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
||||
|
} |
||||
|
|
||||
|
_shapeA = a; |
||||
|
_shapeB = b; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets or sets the A shape parameter of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double A |
||||
|
{ |
||||
|
get { return _shapeA; } |
||||
|
set { SetParameters(value, _shapeB); } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets or sets the B shape parameter of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double B |
||||
|
{ |
||||
|
get { return _shapeB; } |
||||
|
set { SetParameters(_shapeA, value); } |
||||
|
} |
||||
|
|
||||
|
#region IDistribution implementation
|
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets or sets the random number generator which is used to draw random samples.
|
||||
|
/// </summary>
|
||||
|
public Random RandomSource { get; set; } |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the mean of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double Mean |
||||
|
{ |
||||
|
get { return _shapeA / (_shapeA + _shapeB); } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the variance of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double Variance |
||||
|
{ |
||||
|
get { return (_shapeA * _shapeB) / ((_shapeA + _shapeB) * (_shapeA + _shapeB) * (_shapeA + _shapeB + 1.0)); } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the standard deviation of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double StdDev |
||||
|
{ |
||||
|
get { return Math.Sqrt((_shapeA * _shapeB) / ((_shapeA + _shapeB) * (_shapeA + _shapeB) * (_shapeA + _shapeB + 1.0))); } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the entropy of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double Entropy |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
return SpecialFunctions.BetaLn(_shapeA, _shapeB) |
||||
|
- (_shapeA - 1.0) * SpecialFunctions.DiGamma(_shapeA) |
||||
|
- (_shapeB - 1.0) * SpecialFunctions.DiGamma(_shapeB) |
||||
|
+ (_shapeA + _shapeB - 2.0) * SpecialFunctions.DiGamma(_shapeA + _shapeB); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the skewness of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double Skewness |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
return 2.0 * (_shapeB - _shapeA) * Math.Sqrt(_shapeA + _shapeB + 1.0) |
||||
|
/ ((_shapeA + _shapeB + 2.0) * Math.Sqrt(_shapeA * _shapeB)); |
||||
|
} |
||||
|
} |
||||
|
#endregion
|
||||
|
|
||||
|
#region IContinuousDistribution implementation
|
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the mode of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double Mode |
||||
|
{ |
||||
|
get { return (_shapeA - 1) / (_shapeA + _shapeB - 2); } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the median of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double Median |
||||
|
{ |
||||
|
get { throw new NotSupportedException(); } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the minimum of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double Minimum |
||||
|
{ |
||||
|
get { return 0.0; } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the maximum of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
public double Maximum |
||||
|
{ |
||||
|
get { return 1.0; } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Computes the density of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="x">The location at which to compute the density.</param>
|
||||
|
/// <returns>the density at <paramref name="x"/>.</returns>
|
||||
|
public double Density(double x) |
||||
|
{ |
||||
|
double b = SpecialFunctions.Gamma(_shapeA + _shapeB) / (SpecialFunctions.Gamma(_shapeA) * SpecialFunctions.Gamma(_shapeB)); |
||||
|
return b * Math.Pow(x, _shapeA - 1.0) * Math.Pow(1.0 - x, _shapeB - 1.0); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Computes the log density of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="x">The location at which to compute the log density.</param>
|
||||
|
/// <returns>the log density at <paramref name="x"/>.</returns>
|
||||
|
public double DensityLn(double x) |
||||
|
{ |
||||
|
double b = SpecialFunctions.GammaLn(_shapeA + _shapeB) - SpecialFunctions.GammaLn(_shapeA) - SpecialFunctions.GammaLn(_shapeB); |
||||
|
return b + (_shapeA - 1.0)*Math.Log(x) + (_shapeB - 1.0)*Math.Log(1.0 - x); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Computes the cumulative distribution function of the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="x">The location at which to compute the cumulative density.</param>
|
||||
|
/// <returns>the cumulative density at <paramref name="x"/>.</returns>
|
||||
|
public double CumulativeDistribution(double x) |
||||
|
{ |
||||
|
return SpecialFunctions.BetaRegularized(_shapeA, _shapeB, x); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Generates a sample from the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
/// <returns>a sample from the distribution.</returns>
|
||||
|
public double Sample() |
||||
|
{ |
||||
|
return SampleBeta(RandomSource, _shapeA, _shapeB); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Generates a sequence of samples from the Beta distribution.
|
||||
|
/// </summary>
|
||||
|
/// <returns>a sequence of samples from the distribution.</returns>
|
||||
|
public IEnumerable<double> Samples() |
||||
|
{ |
||||
|
while (true) |
||||
|
{ |
||||
|
yield return SampleBeta(RandomSource, _shapeA, _shapeB); |
||||
|
} |
||||
|
} |
||||
|
#endregion
|
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Generates a sample from the normal distribution using the <i>Box-Muller</i> algorithm.
|
||||
|
/// </summary>
|
||||
|
/// <param name="rng">The random number generator to use.</param>
|
||||
|
/// <param name="a">The a shape parameter of the Beta distribution.</param>
|
||||
|
/// <param name="b">The b shape parameter of the Beta distribution.</param>
|
||||
|
/// <returns>a sample from the distribution.</returns>
|
||||
|
public static double Sample(Random rng, double a, double b) |
||||
|
{ |
||||
|
if (Control.CheckDistributionParameters && !IsValidParameterSet(a, b)) |
||||
|
{ |
||||
|
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
||||
|
} |
||||
|
|
||||
|
return SampleBeta(rng, a, b); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Generates a sequence of samples from the normal distribution using the <i>Box-Muller</i> algorithm.
|
||||
|
/// </summary>
|
||||
|
/// <param name="rng">The random number generator to use.</param>
|
||||
|
/// <param name="a">The a shape parameter of the Beta distribution.</param>
|
||||
|
/// <param name="b">The b shape parameter of the Beta distribution.</param>
|
||||
|
/// <returns>a sequence of samples from the distribution.</returns>
|
||||
|
public static IEnumerable<double> Samples(Random rng, double a, double b) |
||||
|
{ |
||||
|
if (Control.CheckDistributionParameters && !IsValidParameterSet(a, b)) |
||||
|
{ |
||||
|
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
||||
|
} |
||||
|
|
||||
|
while (true) |
||||
|
{ |
||||
|
yield return SampleBeta(rng, a, b); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Samples Beta distributed random variables by sampling two Gamma variables and normalizing.
|
||||
|
/// </summary>
|
||||
|
/// <param name="rnd">The random number generator to use.</param>
|
||||
|
/// <param name="a">The A shape parameter.</param>
|
||||
|
/// <param name="b">The B shape parameter.</param>
|
||||
|
/// <returns>a random number from the Beta distribution.</returns>
|
||||
|
internal static double SampleBeta(Random rnd, double a, double b) |
||||
|
{ |
||||
|
double x = Gamma.SampleGamma(rnd, a, 1.0); |
||||
|
double y = Gamma.SampleGamma(rnd, b, 1.0); |
||||
|
return x / (x + y); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
@ -0,0 +1,504 @@ |
|||||
|
// <copyright file="Gamma.cs" company="Math.NET">
|
||||
|
// Math.NET Numerics, part of the Math.NET Project
|
||||
|
// http://mathnet.opensourcedotnet.info
|
||||
|
//
|
||||
|
// Copyright (c) 2009 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.
|
||||
|
// </copyright>
|
||||
|
|
||||
|
namespace MathNet.Numerics.Distributions |
||||
|
{ |
||||
|
using System; |
||||
|
using System.Collections.Generic; |
||||
|
using Properties; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Implements the univariate Gamma distribution. For details about this distribution, see
|
||||
|
/// <a href="http://en.wikipedia.org/wiki/Gamma_distribution">Wikipedia - Gamma distribution</a>.
|
||||
|
/// </summary>
|
||||
|
/// <remarks>
|
||||
|
/// <para>The Gamma distribution is parametrized by a shape and inverse scale parameter. When we want
|
||||
|
/// to specify a Gamma distribution which is a point distribution we set the shape parameter to be the
|
||||
|
/// location of the point distribution and the inverse scale as positive infinity.</para>
|
||||
|
/// <para> Random number generation for the Gamma distribution is based on the algorithm in:
|
||||
|
/// "A Simple Method for Generating Gamma Variables" - Marsaglia & Tsang
|
||||
|
/// ACM Transactions on Mathematical Software, Vol. 26, No. 3, September 2000, Pages 363–372.</para>
|
||||
|
/// <para>The distribution will use the <see cref="System.Random"/> by default.
|
||||
|
/// Users can get/set the random number generator by using the <see cref="RandomSource"/> property.</para>
|
||||
|
/// <para>The statistics classes will check all the incoming parameters whether they are in the allowed
|
||||
|
/// range. This might involve heavy computation. Optionally, by setting Control.CheckDistributionParameters
|
||||
|
/// to false, all parameter checks can be turned off.</para></remarks>
|
||||
|
public class Gamma : IContinuousDistribution |
||||
|
{ |
||||
|
/// <summary>
|
||||
|
/// Gamma shape parameter.
|
||||
|
/// </summary>
|
||||
|
private double _shape; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gamma inverse scale parameter.
|
||||
|
/// </summary>
|
||||
|
private double _invScale; |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Initializes a new instance of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="shape">The shape of the Gamma distribution.</param>
|
||||
|
/// <param name="invScale">The inverse scale of the Gamma distribution.</param>
|
||||
|
public Gamma(double shape, double invScale) |
||||
|
{ |
||||
|
SetParameters(shape, invScale); |
||||
|
RandomSource = new Random(); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Constructs a Gamma distribution from a shape and scale parameter. The distribution will
|
||||
|
/// be initialized with the default <seealso cref="System.Random"/> random number generator.
|
||||
|
/// </summary>
|
||||
|
/// <param name="shape">The shape of the Gamma distribution.</param>
|
||||
|
/// <param name="scale">The scale of the Gamma distribution.</param>
|
||||
|
/// <returns>a normal distribution.</returns>
|
||||
|
public static Gamma WithShapeScale(double shape, double scale) |
||||
|
{ |
||||
|
return new Gamma(shape, 1.0/scale); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Constructs a Gamma distribution from a shape and inverse scale parameter. The distribution will
|
||||
|
/// be initialized with the default <seealso cref="System.Random"/> random number generator.
|
||||
|
/// </summary>
|
||||
|
/// <param name="shape">The shape of the Gamma distribution.</param>
|
||||
|
/// <param name="invScale">The inverse scale of the Gamma distribution.</param>
|
||||
|
/// <returns>a normal distribution.</returns>
|
||||
|
public static Gamma WithShapeInvScale(double shape, double invScale) |
||||
|
{ |
||||
|
return new Gamma(shape, invScale); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// A string representation of the distribution.
|
||||
|
/// </summary>
|
||||
|
/// <returns>a string representation of the distribution.</returns>
|
||||
|
public override string ToString() |
||||
|
{ |
||||
|
return "Gamma(Shape = " + _shape + ", Inverse Scale = " + _invScale + ")"; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Checks whether the parameters of the distribution are valid.
|
||||
|
/// </summary>
|
||||
|
/// <param name="shape">The shape of the Gamma distribution.</param>
|
||||
|
/// <param name="invScale">The inverse scale of the Gamma distribution.</param>
|
||||
|
/// <returns>True when the parameters are valid, false otherwise.</returns>
|
||||
|
private static bool IsValidParameterSet(double shape, double invScale) |
||||
|
{ |
||||
|
if (shape < 0.0 || invScale < 0.0 || Double.IsNaN(shape) || Double.IsNaN(invScale)) |
||||
|
{ |
||||
|
return false; |
||||
|
} |
||||
|
|
||||
|
return true; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Sets the parameters of the distribution after checking their validity.
|
||||
|
/// </summary>
|
||||
|
/// <param name="shape">The shape of the Gamma distribution.</param>
|
||||
|
/// <param name="invScale">The inverse scale of the Gamma distribution.</param>
|
||||
|
/// <exception cref="ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
|
||||
|
private void SetParameters(double shape, double invScale) |
||||
|
{ |
||||
|
if (Control.CheckDistributionParameters && !IsValidParameterSet(shape, invScale)) |
||||
|
{ |
||||
|
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
||||
|
} |
||||
|
|
||||
|
_shape = shape; |
||||
|
_invScale = invScale; |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets or sets the shape of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Shape |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
return _shape; |
||||
|
} |
||||
|
|
||||
|
set |
||||
|
{ |
||||
|
SetParameters(value, _invScale); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets or sets the scale of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Scale |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
return 1.0 / _invScale; |
||||
|
} |
||||
|
|
||||
|
set |
||||
|
{ |
||||
|
SetParameters(_shape, 1.0/value); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets or sets the inverse scale of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double InvScale |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
return _invScale; |
||||
|
} |
||||
|
|
||||
|
set |
||||
|
{ |
||||
|
SetParameters(_shape, value); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
#region IDistribution implementation
|
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets or sets the random number generator which is used to draw random samples.
|
||||
|
/// </summary>
|
||||
|
public Random RandomSource { get; set; } |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the mean of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Mean |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(_invScale)) |
||||
|
{ |
||||
|
return _shape; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return _shape / _invScale; |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the variance of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Variance |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(_invScale)) |
||||
|
{ |
||||
|
return 0.0; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return _shape / (_invScale * _invScale); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the standard deviation of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double StdDev |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(_invScale)) |
||||
|
{ |
||||
|
return 0.0; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return Math.Sqrt(_shape / (_invScale * _invScale)); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the entropy of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Entropy |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(_invScale)) |
||||
|
{ |
||||
|
return 0.0; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return _shape - Math.Log(_invScale) + SpecialFunctions.GammaLn(_shape) + (1.0 - _shape) * SpecialFunctions.DiGamma(_shape); |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the skewness of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Skewness |
||||
|
{ |
||||
|
get { return 2.0 / Math.Sqrt(_shape); } |
||||
|
} |
||||
|
#endregion
|
||||
|
|
||||
|
#region IContinuousDistribution implementation
|
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the mode of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Mode |
||||
|
{ |
||||
|
get |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(_invScale)) |
||||
|
{ |
||||
|
return _shape; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return (_shape - 1.0) / _invScale; |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the median of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Median |
||||
|
{ |
||||
|
get { throw new NotSupportedException(); } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the minimum of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Minimum |
||||
|
{ |
||||
|
get { return 0.0; } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Gets the maximum of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
public double Maximum |
||||
|
{ |
||||
|
get { return Double.PositiveInfinity; } |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Computes the density of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="x">The location at which to compute the density.</param>
|
||||
|
/// <returns>the density at <paramref name="x"/>.</returns>
|
||||
|
public double Density(double x) |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(_invScale)) |
||||
|
{ |
||||
|
if (x == _shape) |
||||
|
{ |
||||
|
return Double.PositiveInfinity; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return 0.0; |
||||
|
} |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return Math.Pow(_invScale, _shape) * Math.Pow(x, _shape - 1.0) * Math.Exp(-_invScale * x) / SpecialFunctions.Gamma(_shape); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Computes the log density of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="x">The location at which to compute the log density.</param>
|
||||
|
/// <returns>the log density at <paramref name="x"/>.</returns>
|
||||
|
public double DensityLn(double x) |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(_invScale)) |
||||
|
{ |
||||
|
if (x == _shape) |
||||
|
{ |
||||
|
return Double.PositiveInfinity; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return Double.NegativeInfinity; |
||||
|
} |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return _shape * Math.Log(_invScale) + (_shape - 1.0) * Math.Log(x) - _invScale * x - SpecialFunctions.GammaLn(_shape); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Computes the cumulative distribution function of the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="x">The location at which to compute the cumulative density.</param>
|
||||
|
/// <returns>the cumulative density at <paramref name="x"/>.</returns>
|
||||
|
public double CumulativeDistribution(double x) |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(_invScale)) |
||||
|
{ |
||||
|
if (x >= _shape) |
||||
|
{ |
||||
|
return 1.0; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return 0.0; |
||||
|
} |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
return SpecialFunctions.IncompleteGamma(_shape, x * _invScale, true); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Generates a sample from the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
/// <returns>a sample from the distribution.</returns>
|
||||
|
public double Sample() |
||||
|
{ |
||||
|
return SampleGamma(RandomSource, _shape, _invScale); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Generates a sequence of samples from the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
/// <returns>a sequence of samples from the distribution.</returns>
|
||||
|
public IEnumerable<double> Samples() |
||||
|
{ |
||||
|
while (true) |
||||
|
{ |
||||
|
yield return SampleGamma(RandomSource, _shape, _invScale); |
||||
|
} |
||||
|
} |
||||
|
#endregion
|
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Generates a sample from the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="rng">The random number generator to use.</param>
|
||||
|
/// <param name="shape">The shape of the Gamma distribution from which to generate samples.</param>
|
||||
|
/// <param name="invScale">The inverse scale of the Gamma distribution from which to generate samples.</param>
|
||||
|
/// <returns>a sample from the distribution.</returns>
|
||||
|
public static double Sample(Random rng, double shape, double invScale) |
||||
|
{ |
||||
|
if (Control.CheckDistributionParameters && !IsValidParameterSet(shape, invScale)) |
||||
|
{ |
||||
|
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
||||
|
} |
||||
|
|
||||
|
return SampleGamma(rng, shape, invScale); |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Generates a sequence of samples from the Gamma distribution.
|
||||
|
/// </summary>
|
||||
|
/// <param name="rng">The random number generator to use.</param>
|
||||
|
/// <param name="shape">The shape of the Gamma distribution from which to generate samples.</param>
|
||||
|
/// <param name="invScale">The inverse scale of the Gamma distribution from which to generate samples.</param>
|
||||
|
/// <returns>a sequence of samples from the distribution.</returns>
|
||||
|
public static IEnumerable<double> Samples(Random rng, double shape, double invScale) |
||||
|
{ |
||||
|
if (Control.CheckDistributionParameters && !IsValidParameterSet(shape, invScale)) |
||||
|
{ |
||||
|
throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
||||
|
} |
||||
|
|
||||
|
while (true) |
||||
|
{ |
||||
|
yield return SampleGamma(rng, shape, invScale); |
||||
|
} |
||||
|
} |
||||
|
|
||||
|
/// <summary>
|
||||
|
/// Sampling implementation based on:
|
||||
|
/// "A Simple Method for Generating Gamma Variables" - Marsaglia & Tsang
|
||||
|
/// ACM Transactions on Mathematical Software, Vol. 26, No. 3, September 2000, Pages 363–372.
|
||||
|
/// </summary>
|
||||
|
/// <param name="rnd">The random number generator to use.</param>
|
||||
|
/// <param name="shape">The shape of the Gamma distribution.</param>
|
||||
|
/// <param name="invScale">The inverse scale of the Gamma distribution.</param>
|
||||
|
/// <returns>A sample from a Gamma distributed random variable.</returns>
|
||||
|
internal static double SampleGamma(System.Random rnd, double shape, double invScale) |
||||
|
{ |
||||
|
if (Double.IsPositiveInfinity(invScale)) |
||||
|
{ |
||||
|
return shape; |
||||
|
} |
||||
|
else |
||||
|
{ |
||||
|
double a = shape; |
||||
|
double alphafix = 1.0; |
||||
|
|
||||
|
// Fix when alpha is less than one.
|
||||
|
if (shape < 1.0) |
||||
|
{ |
||||
|
a = shape + 1.0; |
||||
|
alphafix = System.Math.Pow(rnd.NextDouble(), 1.0 / shape); |
||||
|
} |
||||
|
|
||||
|
double d = a - 1.0 / 3.0; |
||||
|
double c = 1.0 / System.Math.Sqrt(9.0 * d); |
||||
|
while (true) |
||||
|
{ |
||||
|
double x = Normal.Sample(rnd, 0.0, 1.0); |
||||
|
double v = 1.0 + c * x; |
||||
|
while (v <= 0.0) |
||||
|
{ |
||||
|
x = Normal.Sample(rnd, 0.0, 1.0); |
||||
|
v = 1.0 + c * x; |
||||
|
} |
||||
|
v = v * v * v; |
||||
|
double u = rnd.NextDouble(); |
||||
|
x = x * x; |
||||
|
if (u < 1.0 - 0.0331 * x * x) |
||||
|
{ |
||||
|
return alphafix * d * v / invScale; |
||||
|
} |
||||
|
if (System.Math.Log(u) < 0.5 * x + d * (1.0 - v + System.Math.Log(v))) |
||||
|
{ |
||||
|
return alphafix * d * v / invScale; |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
} |
||||
|
} |
||||
Loading…
Reference in new issue