Namespaces

Types in MathNet.Numerics.Distributions

Type InverseGamma

Namespace MathNet.Numerics.Distributions

Interfaces IContinuousDistribution

Continuous Univariate Inverse Gamma distribution. The inverse Gamma distribution is a distribution over the positive real numbers parameterized by two positive parameters..

Constructors

Static Functions

Methods

Properties

Public Constructors

InverseGamma(double shape, double scale, Random randomSource)

Initializes a new instance of the InverseGamma class.
Parameters
double shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

Random randomSource

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

InverseGamma(double shape, double scale)

Initializes a new instance of the InverseGamma class.
Parameters
double shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

Public Static Functions

double CDF(double shape, double scale, double x)

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

The shape (α) of the distribution. Range: α > 0.

double scale

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

double x

The location at which to compute the cumulative distribution function.

Return
double

the cumulative distribution at location x.

bool IsValidParameterSet(double shape, double scale)

Tests whether the provided values are valid parameters for this distribution.
Parameters
double shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

double PDF(double shape, double scale, double x)

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

The shape (α) of the distribution. Range: α > 0.

double scale

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

double x

The location at which to compute the density.

Return
double

the density at x.

double PDFLn(double shape, double scale, double x)

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

The shape (α) of the distribution. Range: α > 0.

double scale

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

double x

The location at which to compute the density.

Return
double

the log density at x.

double Sample(Random rnd, double shape, double scale)

Generates a sample from the distribution.
Parameters
Random rnd

The random number generator to use.

double shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

Return
double

a sample from the distribution.

double Sample(double shape, double scale)

Generates a sample from the distribution.
Parameters
double shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

Return
double

a sample from the distribution.

void Samples(Double[] values, double shape, double scale)

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

The array to fill with the samples.

double shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

Return
void

a sequence of samples from the distribution.

IEnumerable<double> Samples(Random rnd, double shape, double scale)

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

The random number generator to use.

double shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

Return
IEnumerable<double>

a sequence of samples from the distribution.

void Samples(Random rnd, Double[] values, double shape, 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 shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

Return
void

a sequence of samples from the distribution.

IEnumerable<double> Samples(double shape, double scale)

Generates a sequence of samples from the distribution.
Parameters
double shape

The shape (α) of the distribution. Range: α > 0.

double scale

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

Return
IEnumerable<double>

a sequence of samples from the distribution.

Public Methods

double CumulativeDistribution(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.

double Density(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.

double DensityLn(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.

bool Equals(object obj)

int GetHashCode()

Type GetType()

double Sample()

Draws a random sample from the distribution.
Return
double

A random number from this distribution.

IEnumerable<double> Samples()

Generates a sequence of samples from the Cauchy distribution.
Return
IEnumerable<double>

a sequence of samples from the distribution.

void Samples(Double[] values)

Fills an array with samples generated from the distribution.

string ToString()

A string representation of the distribution.
Return
string

a string representation of the distribution.

Public Properties

double Entropy get;

Gets the entropy of the distribution.

double Maximum get;

Gets the maximum of the distribution.

double Mean get;

Gets the mean of the distribution.

double Median get;

Gets the median of the distribution.
Throws NotSupportedException.

double Minimum get;

Gets the minimum of the distribution.

double Mode get;

Gets the mode of the distribution.

Random RandomSource get; set;

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

double Scale get;

Gets or sets The scale (β) parameter. Range: β > 0.

double Shape get;

Gets or sets the shape (α) parameter. Range: α > 0.

double Skewness get;

Gets the skewness of the distribution.

double StdDev get;

Gets the standard deviation of the distribution.

double Variance get;

Gets the variance of the distribution.