Assembly: Extreme.Numerics (Extreme.Numerics)
Syntax
| Visual Basic (Declaration) |
|---|
Public Class ChiSquareDistribution _ Inherits GammaDistribution |
| C# |
|---|
public class ChiSquareDistribution : GammaDistribution |
| C++ |
|---|
public ref class ChiSquareDistribution : public GammaDistribution |
Methods
| Icon | Type | Description |
|---|---|---|
  | DistributionFunction(Double, Int32) |
Evaluates the cumulative distribution function
(CDF) of this distribution for the specified value.
|
| DistributionFunction(Double) |
Returns the value of the cumulative probability
distribution function.
|
| Equals(Object) | |
 | Finalize() | |
| GetExpectedHistogram(Double[](), Double) |
Gets a Histogram whose bins contain the expected number of samples
for a given total number of samples.
|
| GetExpectedHistogram(Double, Double, Int32, Double) |
Gets a Histogram whose bins contain the expected number of samples
for a given total number of samples.
|
| GetHashCode() | Serves as a hash function for a particular type. |
| GetRandomVariate(Random, Double) |
Returns a single random variate from a chi square distribution
with the specified degrees of freedom.
|
| GetRandomVariate(Random) |
Returns a random sample from the distribution.
|
| GetRandomVariates(Random, Vector) |
Fills a Vector with random numbers.
|
| GetRandomVariates(Random, Double[]()) |
Fills a Double array with random numbers.
|
| GetRandomVariates(Random, Double[](), Int32, Int32) |
Fills a Double array with random numbers.
|
| GetRandomVariates(Random, Vector, Int32, Int32) |
Fills a Double array with random numbers.
|
| GetType() | Gets the Type of the current instance. |
| InverseDistributionFunction(Double, Double) |
Returns the inverse of the DistributionFunction(Double, Int32).
|
| InverseDistributionFunction(Double) |
Returns the inverse of the DistributionFunction(Double).
|
| MemberwiseClone() | Creates a shallow copy of the current Object. |
| Probability(Double, Double) |
Returns the probability that a sample taken from the
distribution lies inside the specified interval.
|
| ProbabilityDensityFunction(Double) |
Returns the value of the probability density function
(PDF) of this distribution for the specified value.
|
| SurvivorDistributionFunction(Double) |
Evaluates the survivor distribution function
(SDF) of this distribution for the specified value.
|
| ToString() |
Constructors
| Icon | Type | Description |
|---|---|---|
| ChiSquareDistributionNew(Double) |
Constructs a new Chi Squared distribution.
|
Properties
| Icon | Type | Description |
|---|---|---|
 | DegreesOfFreedom |
Gets the degrees of freedom for this chi-square distribution.
|
| InterQuartileRange |
Returns the inter-quartile range of this distribution.
|
| IsSymmetrical |
Gets a value that indicates whether the distribution is known to be symmetrical around the mean.
|
| Kurtosis |
Gets the kurtosis of the distribution.
|
| LocationParameter |
Gets the location parameter for the distribution.
|
| Mean |
Gets the mean or expectation value of the distribution.
|
| ScaleParameter |
Gets the scale parameter for the distribution.
|
| ShapeParameter |
Gets the shape parameter for the distribution.
|
| Skewness |
Gets the skewness of the distribution.
|
| StandardDeviation |
Gets the standard deviation of the distribution.
|
| Variance |
Gets the variance of the distribution.
|
Remarks
The sum of the squares of n indepemdent normal variables with zero mean and unit variance has a chi-squared distribution with n degrees of freedom. This means it also describes the Variance of samples taken from a NormalDistribution.
From this last property, we can see the usefulness of the chi-squared distribution as a test of statistical significance. We can determine the likelihood of obtaining a sample that deviates from the expected value by a specified amount.
The sum of two or more variables that have a chi-squared distribution also has a chi-squared distribution. The number of degrees of freedom of the new distribution equals the sum of the degrees of freedom of the original distributions.
Inheritance Hierarchy
Extreme.Statistics.Distributions.Distribution
Extreme.Statistics.Distributions.ContinuousDistribution
Extreme.Statistics.Distributions.GammaDistribution
Extreme.Statistics.Distributions.ChiSquareDistribution
