## Types in MathNet.Numerics.Distributions

Type FisherSnedecor

Namespace MathNet.Numerics.Distributions

Interfaces IContinuousDistribution

### Public Constructors

#### FisherSnedecor(double d1, double d2, Random randomSource)

Initializes a new instance of the FisherSnedecor class.
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

###### `Random` randomSource

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

#### FisherSnedecor(double d1, double d2)

Initializes a new instance of the FisherSnedecor class.
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

### Public Static Functions

#### doubleCDF(double d1, double d2, double x)

Computes the cumulative distribution (CDF) of the distribution at x, i.e. P(X ≤ x).
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

###### `double` x

The location at which to compute the cumulative distribution function.

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

the cumulative distribution at location x.

#### doubleInvCDF(double d1, double d2, double p)

Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. This is also known as the quantile or percent point function.
WARNING: currently not an explicit implementation, hence slow and unreliable.
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

###### `double` p

The location at which to compute the inverse cumulative density.

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

the inverse cumulative density at p.

#### boolIsValidParameterSet(double d1, double d2)

Tests whether the provided values are valid parameters for this distribution.
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

#### doublePDF(double d1, double d2, double x)

Computes the probability density of the distribution (PDF) at x, i.e. ∂P(X ≤ x)/∂x.
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

###### `double` x

The location at which to compute the density.

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

the density at x.

#### doublePDFLn(double d1, double d2, double x)

Computes the log probability density of the distribution (lnPDF) at x, i.e. ln(∂P(X ≤ x)/∂x).
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

###### `double` x

The location at which to compute the density.

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

the log density at x.

#### doubleSample(double d1, double d2)

Generates a sample from the distribution.
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

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

a sample from the distribution.

#### doubleSample(Random rnd, double d1, double d2)

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

The random number generator to use.

###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

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

a sample from the distribution.

#### IEnumerable<double>Samples(Random rnd, double d1, double d2)

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

The random number generator to use.

###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

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

a sequence of samples from the distribution.

#### IEnumerable<double>Samples(double d1, double d2)

Generates a sequence of samples from the distribution.
##### Parameters
###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

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

a sequence of samples from the distribution.

#### voidSamples(Double[] values, double d1, double d2)

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

The array to fill with the samples.

###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

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

a sequence of samples from the distribution.

#### voidSamples(Random rnd, Double[] values, double d1, double d2)

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.

###### `double` d1

The first degree of freedom (d1) of the distribution. Range: d1 > 0.

###### `double` d2

The second degree of freedom (d2) of the distribution. Range: d2 > 0.

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

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.

#### doubleInverseCumulativeDistribution(double p)

Computes the inverse of the cumulative distribution function (InvCDF) for the distribution at the given probability. This is also known as the quantile or percent point function.
WARNING: currently not an explicit implementation, hence slow and unreliable.
##### Parameters
###### `double` p

The location at which to compute the inverse cumulative density.

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

the inverse cumulative density at p.

#### doubleSample()

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

a sample from the distribution.

#### IEnumerable<double>Samples()

Generates a sequence of samples from the `FisherSnedecor` 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

#### doubleDegreesOfFreedom1 get;

Gets the first degree of freedom (d1) of the distribution. Range: d1 > 0.

#### doubleDegreesOfFreedom2 get;

Gets the second degree of freedom (d2) of the distribution. Range: d2 > 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.