Chi |
public class ChiSquareDistribution : GammaDistribution
The ChiSquareDistribution type exposes the following members.
| Name | Description | |
|---|---|---|
| ChiSquareDistribution(Double) | Initializes a new instance of the ChiSquareDistribution class. | |
| ChiSquareDistribution(Double, RandomGenerator) | Initializes a new instance of the ChiSquareDistribution class. |
| Name | Description | |
|---|---|---|
| Freedom | Gets the degrees of freedom. | |
| Generator | Returns the random generator used by the distribution to generate the random values. (Inherited from ProbabilityDistribution) | |
| Location | Gets the inverse scale parameter of the distribution. (Inherited from GammaDistribution) | |
| Order | Gets the shape parameter of the distribution. (Inherited from GammaDistribution) |
| Name | Description | |
|---|---|---|
| CDF |
Gives the cumulative probability at x.
(Overrides GammaDistributionCDF(Double)) | |
| Equals | Determines whether the specified object is equal to the current object. (Inherited from Object) | |
| Finalize | Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object) | |
| GetHashCode | Serves as the default hash function. (Inherited from Object) | |
| GetType | Gets the Type of the current instance. (Inherited from Object) | |
| Initialize | Initializes the parameters for the gamma distribution. (Inherited from GammaDistribution) | |
| MemberwiseClone | Creates a shallow copy of the current Object. (Inherited from Object) | |
| NextDouble | Generates the next chi-square distributed random value. | |
|
Gives the probability density at x.
(Overrides GammaDistributionPDF(Double)) | ||
| Quantile |
Gives the pth quantile of the distribution.
(Overrides GammaDistributionQuantile(Double)) | |
| ToString | Returns a string that represents the current object. (Inherited from Object) |
| Name | Description | |
|---|---|---|
| _invTheta |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| algorithmGD |
Cached flag indicating whether algorithm GD is used.
(Inherited from GammaDistribution) | |
| alpha |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| b |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| c |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| d |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| exponentialDistribution |
Cached exponential helper distribution used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| F | Cached degrees of freedom. | |
| generator | Pointer to generator. (Inherited from ProbabilityDistribution) | |
| normalDistribution |
Cached helper distributions used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| q0 |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| r |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| s |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| s2 |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| scale |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) | |
| si |
Cached coefficients used by the gamma distribution implementation.
(Inherited from GammaDistribution) |
Generates random deviates from a central chi-square distribution with
f degrees of freedom. f must be positive.
The density of this distribution is:
-f/2 f/2-1 -x/2
2 x e
p (x) dx = --------------------- dx for x > 0
f Gamma(f/2)
= 0 otherwise
The calculation uses the relation between chi-square and gamma distribution:
ChiSquare(f) = GammaDistribution(f/2,1/2)
References:
K. Behnen, G. Neuhaus, "Grundkurs Stochastik", Teubner Studienbücher
Mathematik, Teubner Verlag, Stuttgart, 1984.