## Types in MathNet.Numerics.Distributions

Type Logistic

Namespace MathNet.Numerics.Distributions

Interfaces IContinuousDistribution

Continuous Univariate Logistic distribution. For details about this distribution, see.

### Public Constructors

#### Logistic(double mean, double scale, Random randomSource)

Initializes a new instance of the Logistic class with a particular mean and standard deviation. The distribution will be initialized with the default random number generator.
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

###### `Random` randomSource

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

#### Logistic(Random randomSource)

Initializes a new instance of the Logistic class. This is a logistic distribution with mean 0.0 and scale 1.0. The distribution will be initialized with the default random number generator.
##### Parameters
###### `Random` randomSource

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

#### Logistic()

Initializes a new instance of the Logistic class. This is a logistic distribution with mean 0.0 and scale 1.0. The distribution will be initialized with the default random number generator.

#### Logistic(double mean, double scale)

Initializes a new instance of the Logistic class with a particular mean and scale parameter. The distribution will be initialized with the default random number generator.
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

### Public Static Functions

#### doubleCDF(double mean, double scale, double x)

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

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

###### `double` x

The location at which to compute the cumulative distribution function.

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

the cumulative distribution at location x.

#### doubleInvCDF(double mean, double scale, 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.
MATLAB: norminv
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

###### `double` p

The location at which to compute the inverse cumulative density.

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

the inverse cumulative density at p.

#### boolIsValidParameterSet(double mean, double scale)

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

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

#### doublePDF(double mean, double scale, double x)

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

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

###### `double` x

The location at which to compute the density.

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

the density at x.

#### doublePDFLn(double mean, double scale, double x)

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

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

###### `double` x

The location at which to compute the density.

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

the log density at x.

#### doubleSample(Random rnd, double mean, double scale)

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

The random number generator to use.

###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

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

a sample from the distribution.

#### doubleSample(double mean, double scale)

Generates a sample from the logistic distribution using the algorithm.
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

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

a sample from the distribution.

#### IEnumerable<double>Samples(Random rnd, double mean, double scale)

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

The random number generator to use.

###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

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

a sequence of samples from the distribution.

#### voidSamples(Random rnd, Double[] values, double mean, double scale)

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` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

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

a sequence of samples from the distribution.

#### IEnumerable<double>Samples(double mean, double scale)

Generates a sequence of samples from the logistic distribution using the algorithm.
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

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

a sequence of samples from the distribution.

#### voidSamples(Double[] values, double mean, double scale)

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

The array to fill with the samples.

###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

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

a sequence of samples from the distribution.

#### LogisticWithMeanPrecision(double mean, double precision, Random randomSource)

Constructs a logistic distribution from a mean and precision.
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` precision

The precision of the logistic distribution. Range: precision > 0.

###### `Random` randomSource

The random number generator which is used to draw random samples. Optional, can be null.

##### Return
###### `Logistic`

A logistic distribution.

#### LogisticWithMeanScale(double mean, double scale, Random randomSource)

Constructs a logistic distribution from a mean and scale parameter.
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` scale

The scale (s) of the logistic distribution. Range: s > 0.

###### `Random` randomSource

The random number generator which is used to draw random samples. Optional, can be null.

##### Return
###### `Logistic`

a logistic distribution.

#### LogisticWithMeanStdDev(double mean, double stddev, Random randomSource)

Constructs a logistic distribution from a mean and standard deviation.
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` stddev

The standard deviation (σ) of the logistic distribution. Range: σ > 0.

###### `Random` randomSource

The random number generator which is used to draw random samples. Optional, can be null.

##### Return
###### `Logistic`

a logistic distribution.

#### LogisticWithMeanVariance(double mean, double var, Random randomSource)

Constructs a logistic distribution from a mean and variance.
##### Parameters
###### `double` mean

The mean (μ) of the logistic distribution.

###### `double` var

The variance (σ^2) of the logistic distribution. Range: (σ^2) > 0.

###### `Random` randomSource

The random number generator which is used to draw random samples. Optional, can be null.

##### Return
###### `Logistic`

A logistic 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.
##### 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 logistic distribution using the algorithm.
##### Return
###### `double`

a sample from the distribution.

#### voidSamples(Double[] values)

Fills an array with samples generated from the distribution.

#### IEnumerable<double>Samples()

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

a sequence of samples from the distribution.

#### stringToString()

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

a string representation of the distribution.

### Public Properties

#### doubleEntropy get;

Gets the entropy of the logistic distribution.

#### doubleMaximum get;

Gets the maximum of the logistic distribution.

#### doubleMean get;

Gets the mean (μ) of the logistic distribution.

#### doubleMedian get;

Gets the median of the logistic distribution.

#### doubleMinimum get;

Gets the minimum of the logistic distribution.

#### doubleMode get;

Gets the mode of the logistic distribution.

#### doublePrecision get;

Gets the precision of the logistic distribution.

#### RandomRandomSource get; set;

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

#### doubleScale get;

Gets the scale parameter of the Logistic distribution. Range: s > 0.

#### doubleSkewness get;

Gets the skewness of the logistic distribution.

#### doubleStdDev get;

Gets the standard deviation (σ) of the logistic distribution. Range: σ > 0.

#### doubleVariance get;

Gets the variance of the logistic distribution.