## Types in MathNet.Numerics.Distributions

Type Chi

Namespace MathNet.Numerics.Distributions

Interfaces IContinuousDistribution

Continuous Univariate Chi distribution. This distribution is a continuous probability distribution. The distribution usually arises when a k-dimensional vector's orthogonal components are independent and each follow a standard normal distribution. The length of the vector will then have a chi distribution..

### Public Constructors

#### Chi(double freedom, Random randomSource)

Initializes a new instance of the Chi class.
##### Parameters
###### `double` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

###### `Random` randomSource

The random number generator which is used to draw random samples.

#### Chi(double freedom)

Initializes a new instance of the Chi class.
##### Parameters
###### `double` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

### Public Static Functions

#### doubleCDF(double freedom, double x)

Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
##### Parameters
###### `double` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

###### `double` x

The location at which to compute the cumulative distribution function.

##### Return
###### `double`

the cumulative distribution at location x.

#### boolIsValidParameterSet(double freedom)

Tests whether the provided values are valid parameters for this distribution.
##### Parameters
###### `double` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

#### doublePDF(double freedom, double x)

Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
##### Parameters
###### `double` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

###### `double` x

The location at which to compute the density.

##### Return
###### `double`

the density at x.

#### doublePDFLn(double freedom, double x)

Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
##### Parameters
###### `double` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

###### `double` x

The location at which to compute the density.

##### Return
###### `double`

the log density at x.

#### doubleSample(Random rnd, int freedom)

Generates a sample from the distribution.
##### Parameters
###### `Random` rnd

The random number generator to use.

###### `int` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

##### Return
###### `double`

a sample from the distribution.

#### doubleSample(int freedom)

Generates a sample from the distribution.
##### Parameters
###### `int` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

##### Return
###### `double`

a sample from the distribution.

#### voidSamples(Double[] values, int freedom)

Fills an array with samples generated from the distribution.
##### Parameters
###### `Double[]` values

The array to fill with the samples.

###### `int` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

##### Return
###### `void`

a sequence of samples from the distribution.

#### IEnumerable<double>Samples(Random rnd, int freedom)

Generates a sequence of samples from the distribution.
##### Parameters
###### `Random` rnd

The random number generator to use.

###### `int` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

##### Return
###### `IEnumerable<double>`

a sequence of samples from the distribution.

#### voidSamples(Random rnd, Double[] values, int freedom)

Fills an array with samples generated from the distribution.
##### Parameters
###### `Random` rnd

The random number generator to use.

###### `Double[]` values

The array to fill with the samples.

###### `int` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

##### Return
###### `void`

a sequence of samples from the distribution.

#### IEnumerable<double>Samples(int freedom)

Generates a sequence of samples from the distribution.
##### Parameters
###### `int` freedom

The degrees of freedom (k) of the distribution. Range: k > 0.

##### Return
###### `IEnumerable<double>`

a sequence of samples from the distribution.

### Public Methods

#### doubleCumulativeDistribution(double x)

Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
##### Parameters
###### `double` x

The location at which to compute the cumulative distribution function.

##### Return
###### `double`

the cumulative distribution at location x.

#### doubleDensity(double x)

Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
##### Parameters
###### `double` x

The location at which to compute the density.

##### Return
###### `double`

the density at x.

#### doubleDensityLn(double x)

Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
##### Parameters
###### `double` x

The location at which to compute the log density.

##### Return
###### `double`

the log density at x.

#### doubleSample()

Generates a sample from the Chi distribution.
##### Return
###### `double`

a sample from the distribution.

#### IEnumerable<double>Samples()

Generates a sequence of samples from the Chi distribution.
##### Return
###### `IEnumerable<double>`

a sequence of samples from the distribution.

#### voidSamples(Double[] values)

Fills an array with samples generated from the distribution.

#### stringToString()

A string representation of the distribution.
##### Return
###### `string`

a string representation of the distribution.

### Public Properties

#### doubleDegreesOfFreedom get;

Gets the degrees of freedom (k) of the Chi distribution. Range: k > 0.

#### doubleEntropy get;

Gets the entropy of the distribution.

#### doubleMaximum get;

Gets the maximum of the distribution.

#### doubleMean get;

Gets the mean of the distribution.

#### doubleMedian get;

Gets the median of the distribution.

#### doubleMinimum get;

Gets the minimum of the distribution.

#### doubleMode get;

Gets the mode of the distribution.

#### RandomRandomSource get; set;

Gets or sets the random number generator which is used to draw random samples.

#### doubleSkewness get;

Gets the skewness of the distribution.

#### doubleStdDev get;

Gets the standard deviation of the distribution.

#### doubleVariance get;

Gets the variance of the distribution.