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