C# Class Accord.Statistics.Distributions.Multivariate.WishartDistribution

Inheritance: MultivariateContinuousDistribution

Public Methods

Method	Description
Clone ( ) : object	Creates a new object that is a copy of the current instance.
DistributionFunction ( ) : double	Unsupported.
Fit ( double observations, double weights, Fitting options ) : void	Fits the underlying distribution to a given set of observations.
LogProbabilityDensityFunction ( ) : double	Gets the log-probability density function (pdf) for this distribution evaluated at point `x`.
LogProbabilityDensityFunction ( double x ) : double	Gets the log-probability density function (pdf) for this distribution evaluated at point `x`.
ProbabilityDensityFunction ( ) : double	Gets the probability density function (pdf) for this distribution evaluated at point `x`. The Probability Density Function (PDF) describes the probability that a given value `x` will occur.
ProbabilityDensityFunction ( double x ) : double	Gets the probability density function (pdf) for this distribution evaluated at point `x`. The Probability Density Function (PDF) describes the probability that a given value `x` will occur.
ToString ( string format, IFormatProvider formatProvider ) : string	Returns a System.String that represents this instance.
WishartDistribution ( double degreesOfFreedom, double scale ) : System	Creates a new Wishart distribution.

Creates a new object that is a copy of the current instance.

public Clone ( ) : object
return	object

Unsupported.

public DistributionFunction ( ) : double
return	double

Fits the underlying distribution to a given set of observations.

public Fit ( double observations, double weights, Fitting options ) : void
observations	double	The array of observations to fit the model against. The array /// elements can be either of type double (for univariate data) or /// type double[] (for multivariate data).
weights	double	The weight vector containing the weight for each of the samples.
options	Fitting	Optional arguments which may be used during fitting, such /// as regularization constants and additional parameters.
return	void

Gets the log-probability density function (pdf) for this distribution evaluated at point x.

public LogProbabilityDensityFunction ( ) : double
return	double

Gets the log-probability density function (pdf) for this distribution evaluated at point x.

public LogProbabilityDensityFunction ( double x ) : double
x	double	A single point in the distribution range. /// For a matrix distribution, such as the Wishart's, this /// should be a positive-definite matrix or a matrix written /// in flat vector form. ///
return	double

Gets the probability density function (pdf) for this distribution evaluated at point x.

The Probability Density Function (PDF) describes the probability that a given value x will occur.

public ProbabilityDensityFunction ( ) : double
return	double

Gets the probability density function (pdf) for this distribution evaluated at point x.

The Probability Density Function (PDF) describes the probability that a given value x will occur.

public ProbabilityDensityFunction ( double x ) : double
x	double	A single point in the distribution range. /// For a matrix distribution, such as the Wishart's, this /// should be a positive-definite matrix or a matrix written /// in flat vector form. ///
return	double

Returns a System.String that represents this instance.

public ToString ( string format, IFormatProvider formatProvider ) : string
format	string	The format.
formatProvider	IFormatProvider	The format provider.
return	string

Creates a new Wishart distribution.

public WishartDistribution ( double degreesOfFreedom, double scale ) : System
degreesOfFreedom	double	The degrees of freedom n.
scale	double	The positive-definite matrix scale matrix V.
return	System