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@ -43,27 +43,21 @@ namespace MathNet.Numerics.Distributions |
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/// <summary>
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/// <summary>
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/// The Poisson distribution parameter λ.
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/// The Poisson distribution parameter λ.
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/// </summary>
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/// </summary>
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private double _lambda; |
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double _lambda; |
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/// <summary>
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/// <summary>
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/// The distribution's random number generator.
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/// The distribution's random number generator.
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/// </summary>
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/// </summary>
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private Random _random; |
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Random _random; |
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/// <summary>
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/// <summary>
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/// Gets or sets the Poisson distribution parameter λ.
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/// Gets or sets the Poisson distribution parameter λ.
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/// </summary>
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/// </summary>
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public double Lambda |
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public double Lambda |
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{ |
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{ |
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get |
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get { return _lambda; } |
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{ |
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return _lambda; |
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} |
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set |
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set { SetParameters(value); } |
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{ |
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SetParameters(value); |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -82,7 +76,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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/// <param name="lambda">The mean (λ) of the distribution.</param>
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/// <param name="lambda">The mean (λ) of the distribution.</param>
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/// <exception cref="System.ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
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/// <exception cref="System.ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
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private void SetParameters(double lambda) |
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void SetParameters(double lambda) |
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{ |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda)) |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda)) |
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{ |
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{ |
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@ -97,7 +91,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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/// <param name="lambda">The mean (λ) of the distribution.</param>
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/// <param name="lambda">The mean (λ) of the distribution.</param>
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/// <returns><c>true</c> when the parameters are valid, <c>false</c> otherwise.</returns>
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/// <returns><c>true</c> when the parameters are valid, <c>false</c> otherwise.</returns>
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private static bool IsValidParameterSet(double lambda) |
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static bool IsValidParameterSet(double lambda) |
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{ |
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{ |
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return lambda > 0.00; |
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return lambda > 0.00; |
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} |
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} |
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@ -120,10 +114,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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public Random RandomSource |
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public Random RandomSource |
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{ |
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{ |
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get |
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get { return _random; } |
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{ |
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return _random; |
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} |
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set |
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set |
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{ |
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{ |
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@ -141,10 +132,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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public double Mean |
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public double Mean |
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{ |
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{ |
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get |
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get { return _lambda; } |
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{ |
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return _lambda; |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -152,10 +140,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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public double Variance |
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public double Variance |
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{ |
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{ |
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get |
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get { return _lambda; } |
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{ |
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return _lambda; |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -163,10 +148,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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public double StdDev |
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public double StdDev |
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{ |
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{ |
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get |
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get { return Math.Sqrt(_lambda); } |
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{ |
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return Math.Sqrt(_lambda); |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -175,10 +157,7 @@ namespace MathNet.Numerics.Distributions |
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/// <remarks>Approximation, see Wikipedia <a href="http://en.wikipedia.org/wiki/Poisson_distribution">Poisson distribution</a></remarks>
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/// <remarks>Approximation, see Wikipedia <a href="http://en.wikipedia.org/wiki/Poisson_distribution">Poisson distribution</a></remarks>
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public double Entropy |
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public double Entropy |
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{ |
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{ |
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get |
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get { return (0.5 * Math.Log(2 * Constants.Pi * Constants.E * _lambda)) - (1.0 / (12.0 * _lambda)) - (1.0 / (24.0 * _lambda * _lambda)) - (19.0 / (360.0 * _lambda * _lambda * _lambda)); } |
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{ |
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return (0.5 * Math.Log(2 * Constants.Pi * Constants.E * _lambda)) - (1.0 / (12.0 * _lambda)) - (1.0 / (24.0 * _lambda * _lambda)) - (19.0 / (360.0 * _lambda * _lambda * _lambda)); |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -186,10 +165,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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public double Skewness |
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public double Skewness |
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{ |
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{ |
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get |
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get { return 1.0 / Math.Sqrt(_lambda); } |
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{ |
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return 1.0 / Math.Sqrt(_lambda); |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -197,10 +173,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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public int Minimum |
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public int Minimum |
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{ |
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{ |
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get |
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get { return 0; } |
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{ |
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return 0; |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -208,10 +181,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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public int Maximum |
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public int Maximum |
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{ |
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{ |
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get |
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get { return int.MaxValue; } |
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{ |
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return int.MaxValue; |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -233,10 +203,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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/// </summary>
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public int Mode |
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public int Mode |
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{ |
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{ |
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get |
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get { return (int)Math.Floor(_lambda); } |
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{ |
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return (int)Math.Floor(_lambda); |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -245,10 +212,7 @@ namespace MathNet.Numerics.Distributions |
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/// <remarks>Approximation, see Wikipedia <a href="http://en.wikipedia.org/wiki/Poisson_distribution">Poisson distribution</a></remarks>
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/// <remarks>Approximation, see Wikipedia <a href="http://en.wikipedia.org/wiki/Poisson_distribution">Poisson distribution</a></remarks>
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public int Median |
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public int Median |
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{ |
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{ |
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get |
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get { return (int)Math.Floor(_lambda + (1.0 / 3.0) - (0.02 / _lambda)); } |
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{ |
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return (int)Math.Floor(_lambda + (1.0 / 3.0) - (0.02 / _lambda)); |
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} |
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} |
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} |
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/// <summary>
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/// <summary>
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@ -271,71 +235,15 @@ namespace MathNet.Numerics.Distributions |
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return -_lambda + (k * Math.Log(_lambda)) - SpecialFunctions.FactorialLn(k); |
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return -_lambda + (k * Math.Log(_lambda)) - SpecialFunctions.FactorialLn(k); |
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} |
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} |
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/// <summary>
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/// Samples a Poisson distributed random variable.
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/// </summary>
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/// <returns>A sample from the Poisson distribution.</returns>
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public int Sample() |
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{ |
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return DoSample(RandomSource, _lambda); |
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} |
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/// <summary>
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/// Samples an array of Poisson distributed random variables.
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/// </summary>
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/// <returns>a sequence of successes in N trials.</returns>
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public IEnumerable<int> Samples() |
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{ |
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while (true) |
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{ |
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yield return DoSample(RandomSource, _lambda); |
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} |
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} |
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#endregion
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#endregion
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/// <summary>
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/// Samples a Poisson distributed random variable.
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/// </summary>
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/// <param name="rnd">The random number generator to use.</param>
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/// <param name="lambda">The Poisson distribution parameter λ.</param>
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/// <returns>A sample from the Poisson distribution.</returns>
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public static int Sample(Random rnd, double lambda) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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return DoSample(rnd, lambda); |
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} |
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/// <summary>
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/// Samples a sequence of Poisson distributed random variables.
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/// </summary>
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/// <param name="rnd">The random number generator to use.</param>
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/// <param name="lambda">The Poisson distribution parameter λ.</param>
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/// <returns>a sequence of samples from the distribution.</returns>
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public static IEnumerable<int> Samples(Random rnd, double lambda) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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while (true) |
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{ |
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yield return DoSample(rnd, lambda); |
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} |
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} |
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/// <summary>
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/// <summary>
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/// Generates one sample from the Poisson distribution.
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/// Generates one sample from the Poisson distribution.
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/// </summary>
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/// </summary>
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/// <param name="rnd">The random source to use.</param>
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/// <param name="rnd">The random source to use.</param>
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/// <param name="lambda">The Poisson distribution parameter λ.</param>
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/// <param name="lambda">The Poisson distribution parameter λ.</param>
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/// <returns>A random sample from the Poisson distribution.</returns>
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/// <returns>A random sample from the Poisson distribution.</returns>
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private static int DoSample(Random rnd, double lambda) |
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internal static int SampleUnchecked(Random rnd, double lambda) |
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{ |
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{ |
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return (lambda < 30.0) ? DoSampleShort(rnd, lambda) : DoSampleLarge(rnd, lambda); |
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return (lambda < 30.0) ? DoSampleShort(rnd, lambda) : DoSampleLarge(rnd, lambda); |
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} |
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} |
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@ -346,7 +254,7 @@ namespace MathNet.Numerics.Distributions |
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/// <param name="rnd">The random source to use.</param>
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/// <param name="rnd">The random source to use.</param>
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/// <param name="lambda">The Poisson distribution parameter λ.</param>
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/// <param name="lambda">The Poisson distribution parameter λ.</param>
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/// <returns>A random sample from the Poisson distribution.</returns>
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/// <returns>A random sample from the Poisson distribution.</returns>
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private static int DoSampleShort(Random rnd, double lambda) |
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static int DoSampleShort(Random rnd, double lambda) |
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{ |
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{ |
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var limit = Math.Exp(-lambda); |
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var limit = Math.Exp(-lambda); |
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var count = 0; |
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var count = 0; |
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@ -367,7 +275,7 @@ namespace MathNet.Numerics.Distributions |
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/// <remarks>"Rejection method PA" from "The Computer Generation of Poisson Random Variables" by A. C. Atkinson,
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/// <remarks>"Rejection method PA" from "The Computer Generation of Poisson Random Variables" by A. C. Atkinson,
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/// Journal of the Royal Statistical Society Series C (Applied Statistics) Vol. 28, No. 1. (1979)
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/// Journal of the Royal Statistical Society Series C (Applied Statistics) Vol. 28, No. 1. (1979)
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/// The article is on pages 29-35. The algorithm given here is on page 32. </remarks>
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/// The article is on pages 29-35. The algorithm given here is on page 32. </remarks>
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private static int DoSampleLarge(Random rnd, double lambda) |
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static int DoSampleLarge(Random rnd, double lambda) |
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{ |
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{ |
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var c = 0.767 - (3.36 / lambda); |
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var c = 0.767 - (3.36 / lambda); |
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var beta = Math.PI / Math.Sqrt(3.0 * lambda); |
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var beta = Math.PI / Math.Sqrt(3.0 * lambda); |
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@ -395,5 +303,61 @@ namespace MathNet.Numerics.Distributions |
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} |
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} |
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} |
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} |
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} |
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} |
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/// <summary>
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/// Samples a Poisson distributed random variable.
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/// </summary>
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/// <returns>A sample from the Poisson distribution.</returns>
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public int Sample() |
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{ |
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return SampleUnchecked(RandomSource, _lambda); |
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} |
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/// <summary>
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/// Samples an array of Poisson distributed random variables.
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/// </summary>
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/// <returns>a sequence of successes in N trials.</returns>
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public IEnumerable<int> Samples() |
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{ |
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while (true) |
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{ |
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yield return SampleUnchecked(RandomSource, _lambda); |
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} |
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} |
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/// <summary>
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/// Samples a Poisson distributed random variable.
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/// </summary>
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/// <param name="rnd">The random number generator to use.</param>
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/// <param name="lambda">The Poisson distribution parameter λ.</param>
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/// <returns>A sample from the Poisson distribution.</returns>
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public static int Sample(Random rnd, double lambda) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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return SampleUnchecked(rnd, lambda); |
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} |
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/// <summary>
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/// Samples a sequence of Poisson distributed random variables.
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/// </summary>
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/// <param name="rnd">The random number generator to use.</param>
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/// <param name="lambda">The Poisson distribution parameter λ.</param>
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/// <returns>a sequence of samples from the distribution.</returns>
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public static IEnumerable<int> Samples(Random rnd, double lambda) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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while (true) |
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{ |
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yield return SampleUnchecked(rnd, lambda); |
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} |
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} |
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} |
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} |
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} |
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} |
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Christoph Ruegg
14 years ago