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@ -52,37 +52,37 @@ namespace MathNet.Numerics.Distributions |
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/// Since many properties of the distribution can only be computed approximately, the tolerance
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/// level specifies how much error we accept.
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/// </summary>
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private const double Tolerance = 1e-12; |
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const double Tolerance = 1e-12; |
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/// <summary>
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/// The mean of the distribution.
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/// </summary>
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private double _mean = double.MinValue; |
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double _mean = double.MinValue; |
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/// <summary>
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/// The variance of the distribution.
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/// </summary>
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private double _variance = double.MinValue; |
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double _variance = double.MinValue; |
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/// <summary>
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/// Caches the value of the normalization constant.
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/// </summary>
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private double _z = double.MinValue; |
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double _z = double.MinValue; |
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/// <summary>
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/// The lambda parameter.
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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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/// The nu parameter.
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/// </summary>
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private double _nu; |
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double _nu; |
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/// <summary>
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/// The distribution's random number generator.
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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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/// Initializes a new instance of the <see cref="ConwayMaxwellPoisson"/> class.
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@ -105,7 +105,7 @@ namespace MathNet.Numerics.Distributions |
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/// <param name="lambda">The lambda parameter.</param>
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/// <param name="nu">The nu parameter.</param>
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/// <exception cref="ArgumentOutOfRangeException">When the parameters don't pass the <see cref="IsValidParameterSet"/> function.</exception>
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private void SetParameters(double lambda, double nu) |
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void SetParameters(double lambda, double nu) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda, nu)) |
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{ |
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@ -122,7 +122,7 @@ namespace MathNet.Numerics.Distributions |
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/// <param name="lambda">The lambda parameter.</param>
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/// <param name="nu">The nu parameter.</param>
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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, double nu) |
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static bool IsValidParameterSet(double lambda, double nu) |
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{ |
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if (lambda <= 0.0) |
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{ |
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@ -143,15 +143,9 @@ namespace MathNet.Numerics.Distributions |
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/// <value>The value of the lambda parameter.</value>
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public double Lambda |
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{ |
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get |
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{ |
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return _lambda; |
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} |
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get { return _lambda; } |
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set |
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{ |
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SetParameters(value, _nu); |
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} |
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set { SetParameters(value, _nu); } |
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} |
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/// <summary>
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@ -160,15 +154,9 @@ namespace MathNet.Numerics.Distributions |
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/// <value>The value of the Nu parameter.</value>
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public double Nu |
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{ |
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get |
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{ |
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return _nu; |
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} |
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get { return _nu; } |
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set |
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{ |
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SetParameters(_lambda, value); |
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} |
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set { SetParameters(_lambda, value); } |
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} |
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/// <summary>
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@ -189,10 +177,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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public Random RandomSource |
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{ |
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get |
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{ |
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return _random; |
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} |
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get { return _random; } |
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set |
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{ |
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@ -333,10 +318,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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public double StdDev |
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{ |
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get |
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{ |
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return Math.Sqrt(Variance); |
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} |
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get { return Math.Sqrt(Variance); } |
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} |
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/// <summary>
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@ -344,10 +326,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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public double Entropy |
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{ |
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get |
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{ |
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throw new NotSupportedException(); |
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} |
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get { throw new NotSupportedException(); } |
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} |
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/// <summary>
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@ -355,10 +334,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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public double Skewness |
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{ |
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get |
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{ |
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throw new NotSupportedException(); |
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} |
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get { throw new NotSupportedException(); } |
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} |
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/// <summary>
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@ -386,10 +362,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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public int Mode |
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{ |
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get |
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{ |
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throw new NotSupportedException(); |
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} |
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get { throw new NotSupportedException(); } |
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} |
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/// <summary>
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@ -397,10 +370,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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public int Median |
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{ |
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get |
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{ |
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throw new NotSupportedException(); |
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} |
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get { throw new NotSupportedException(); } |
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} |
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/// <summary>
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@ -408,10 +378,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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public int Minimum |
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{ |
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get |
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{ |
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return 0; |
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} |
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get { return 0; } |
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} |
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/// <summary>
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@ -419,10 +386,7 @@ namespace MathNet.Numerics.Distributions |
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/// </summary>
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public int Maximum |
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{ |
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get |
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{ |
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throw new NotSupportedException(); |
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} |
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get { throw new NotSupportedException(); } |
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} |
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/// <summary>
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@ -449,35 +413,12 @@ namespace MathNet.Numerics.Distributions |
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return Math.Log(Probability(k)); |
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} |
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/// <summary>
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/// Samples a Conway-Maxwell-Poisson distributed random variable.
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/// </summary>
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/// <returns>a sample from the distribution.</returns>
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public int Sample() |
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{ |
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return DoSample(RandomSource, _lambda, _nu, Z); |
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} |
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/// <summary>
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/// Samples a sequence of a Conway-Maxwell-Poisson distributed random variables.
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/// </summary>
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/// <returns>
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/// a sequence of samples from a Conway-Maxwell-Poisson distribution.
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/// </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, _nu, Z); |
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} |
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} |
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#endregion
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/// <summary>
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/// Gets the normalization constant of the Conway-Maxwell-Poisson distribution.
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/// </summary>
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private double Z |
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double Z |
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{ |
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get |
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{ |
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@ -488,7 +429,7 @@ namespace MathNet.Numerics.Distributions |
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_z = Normalization(_lambda, _nu); |
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return _z; |
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} |
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} |
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} |
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/// <summary>
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@ -499,7 +440,7 @@ namespace MathNet.Numerics.Distributions |
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/// <returns>
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/// an approximate normalization constant for the CMP distribution.
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/// </returns>
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private static double Normalization(double lambda, double nu) |
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static double Normalization(double lambda, double nu) |
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{ |
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// Initialize Z with the first two terms.
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var z = 1.0 + lambda; |
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@ -515,7 +456,7 @@ namespace MathNet.Numerics.Distributions |
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// The new term.
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t = t * e; |
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// The updated normalization constant.
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z = z + t; |
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@ -542,7 +483,7 @@ namespace MathNet.Numerics.Distributions |
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/// <returns>
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/// One sample from the distribution implied by <paramref name="lambda"/>, <paramref name="nu"/>, and <paramref name="z"/>.
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/// </returns>
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private static int DoSample(Random rnd, double lambda, double nu, double z) |
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internal static int SampleUnchecked(Random rnd, double lambda, double nu, double z) |
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{ |
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var u = rnd.NextDouble(); |
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var p = 1.0 / z; |
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@ -558,5 +499,65 @@ namespace MathNet.Numerics.Distributions |
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return i; |
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} |
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/// <summary>
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/// Samples a Conway-Maxwell-Poisson distributed random variable.
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/// </summary>
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/// <returns>a sample from the distribution.</returns>
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public int Sample() |
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{ |
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return SampleUnchecked(RandomSource, _lambda, _nu, Z); |
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} |
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/// <summary>
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/// Samples a sequence of a Conway-Maxwell-Poisson distributed random variables.
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/// </summary>
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/// <returns>
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/// a sequence of samples from a Conway-Maxwell-Poisson distribution.
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/// </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, _nu, Z); |
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} |
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} |
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/// <summary>
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/// Samples a 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 lambda parameter</param>
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/// <param name="nu">The nu parameter.</param>
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public static int Sample(Random rnd, double lambda, double nu) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda, nu)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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var z = Normalization(lambda, nu); |
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return SampleUnchecked(rnd, lambda, nu, z); |
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} |
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/// <summary>
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/// Samples a sequence of this 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 lambda parameter</param>
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/// <param name="nu">The nu parameter.</param>
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public static IEnumerable<int> Samples(Random rnd, double lambda, double nu) |
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{ |
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if (Control.CheckDistributionParameters && !IsValidParameterSet(lambda, nu)) |
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{ |
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throw new ArgumentOutOfRangeException(Resources.InvalidDistributionParameters); |
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} |
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var z = Normalization(lambda, nu); |
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while (true) |
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{ |
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yield return SampleUnchecked(rnd, lambda, nu, z); |
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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