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14 years ago
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// <copyright file="MCMCDiagonistics.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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// http://mathnetnumerics.codeplex.com
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//
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// Copyright (c) 2009-2010 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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using System; |
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using System.Collections.Generic; |
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using System.Linq; |
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using System.Text; |
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using System.Numerics; |
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namespace MathNet.Numerics.Statistics.Mcmc.Diagonistics |
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{ |
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/// <summary>
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/// Provides utilities to analysis the convergence of a set of samples from
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/// a <seealso cref="McmcSampler{T}"/>.
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/// </summary>
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static public class MCMCDiagonistics |
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{ |
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/// <summary>
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/// Computes the auto correlations of a series evaluated by a function f.
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/// </summary>
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/// <param name="Series">The series for computing the auto correlation.</param>
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/// <param name="lag">The lag in the series</param>
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/// <param name="f">The function used to evaluate the series.</param>
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/// <returns>The auto correlation.</returns>
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/// <exception cref="ArgumentOutOfRangeException">Throws if lag is zero or if lag is
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/// greater than or equal to the length of Series.</exception>
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static public double ACF<T>(IEnumerable<T> Series, int lag, Func<T,double> f) |
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{ |
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if (lag < 0) |
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throw new ArgumentOutOfRangeException("Lag must be positive"); |
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int Length = Series.Count(); |
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if (lag >= Length) |
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throw new ArgumentOutOfRangeException("Lag must be smaller than the sample size"); |
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var TransformedSeries = from data in Series |
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select f(data); |
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var FirstSeries = TransformedSeries.Take(Length-lag); |
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var SecondSeries = TransformedSeries.Skip(lag); |
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return Correlation.Pearson(FirstSeries, SecondSeries); |
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} |
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/// <summary>
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/// Computes the effective size of the sample when evaluated by a function f.
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/// </summary>
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/// <param name="Series">The samples.</param>
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/// <param name="f">The function use for evaluating the series.</param>
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/// <returns>The effective size when auto correlation is taken into account.</returns>
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static public double EffectiveSize<T>(IEnumerable<T> Series, Func<T,double> f) |
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{ |
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int Length = Series.Count(); |
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double rho = ACF(Series, 1, f); |
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return ((1 - rho) / (1 + rho)) * Length; |
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} |
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} |
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} |
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@ -1,141 +0,0 @@ |
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// <copyright file="MCMCDiagonistics.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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// http://mathnetnumerics.codeplex.com
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//
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// Copyright (c) 2009-2010 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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using System; |
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using System.Collections.Generic; |
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using System.Linq; |
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using System.Text; |
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using NUnit.Framework; |
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using MathNet.Numerics.Statistics; |
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using MathNet.Numerics.Distributions; |
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using MathNet.Numerics.Statistics.Mcmc.Diagonistics; |
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using MathNet.Numerics.Random; |
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namespace MathNet.Numerics.UnitTests.StatisticsTests.McmcTests |
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{ |
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/// <summary>
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/// MCMCDiagonistics testing.
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/// </summary>
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[TestFixture] |
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public class MCMCDiagonisticsTest |
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{ |
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/// <summary>
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/// For generation of a random series to test the methods.
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/// </summary>
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private System.Random rnd = new System.Random(); |
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/// <summary>
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/// Distribution to sample the entries of the random series from.
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/// </summary>
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private Normal dis = new Normal(0, 1); |
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/// <summary>
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/// Testing the ACF function using a randomly generated series with a range
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/// of lags.
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/// </summary>
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/// <param name="startlag">Minimum value of lag in the test.</param>
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/// <param name="endlag">Maximum value of lag in the test.</param>
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[TestCase(0, 10)] |
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[TestCase(11, 20)] |
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[TestCase(21, 30)] |
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[TestCase(31, 40)] |
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public void TestACF(int startlag, int endlag) |
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{ |
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for (int lag = startlag; lag < endlag; lag++) |
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{ |
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int Length = 10000; |
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double[] firstSeries = new double[Length - lag]; |
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double[] secondSeries = new double[Length - lag]; |
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double[] Series = new double[Length]; |
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for (int i = 0; i < Length; i++) |
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{ Series[i] = RandomSeries(); } |
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double[] TransformedSeries = new double[Length]; |
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for (int i = 0; i < Length; i++) |
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{ TransformedSeries[i] = Series[i] * Series[i]; } |
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Array.Copy(TransformedSeries, firstSeries, Length - lag); |
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Array.Copy(TransformedSeries, lag, secondSeries, 0, Length - lag); |
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double result = MCMCDiagonistics.ACF(Series, lag, x=>x*x); |
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double correlation = Correlation.Pearson(firstSeries, secondSeries); |
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Assert.AreEqual(result, correlation, 10e-13); |
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} |
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} |
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/// <summary>
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/// Set lag to be greater than the length of the series throws a
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/// <c>ArgumentOutOfRangeException</c>.
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/// </summary>
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[Test] |
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public void LagOutOfRange() |
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{ |
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int Length = 10; |
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double[] Series = new double[Length]; |
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Assert.Throws<ArgumentOutOfRangeException>(() => MCMCDiagonistics.ACF(Series, 11, x=>x)); |
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} |
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/// <summary>
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/// Set lag to be negative throws a <c>ArgumentOutOfRangeException</c>.
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/// </summary>
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[Test] |
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public void LagNegative() |
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{ |
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Assert.Throws<ArgumentOutOfRangeException>(() => MCMCDiagonistics.ACF(new double[10], -1, x=>x)); |
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} |
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/// <summary>
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/// Generating a random number used for the entry of the series.
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/// </summary>
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/// <returns>A random number.</returns>
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private double RandomSeries() |
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{ return rnd.NextDouble() + rnd.NextDouble() * (dis.Sample()); } |
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/// <summary>
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/// Testing the effective size using a random series.
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/// </summary>
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[Test] |
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public void EffectiveSizeTest() |
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{ |
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int Length = 10; |
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double[] Series = new double[Length]; |
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for (int i = 0; i < Length; i++) |
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{ Series[i] = RandomSeries(); } |
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double rho = MCMCDiagonistics.ACF(Series, 1,x=>x*x); |
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double ESS = (1 - rho) / (1 + rho) * Length; |
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Assert.AreEqual(ESS, MCMCDiagonistics.EffectiveSize(Series,x=>x*x), 10e-13); |
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} |
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} |
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} |
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