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

Inheritance: MultivariateContinuousDistribution
Exibir arquivo Open project: accord-net/framework Class Usage Examples

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.

Method Details

Clone() public method

Creates a new object that is a copy of the current instance.
public Clone ( ) : object
return object

DistributionFunction() public method

Unsupported.
public DistributionFunction ( ) : double
return double

Fit() public method

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

LogProbabilityDensityFunction() public method

Gets the log-probability density function (pdf) for this distribution evaluated at point x.
public LogProbabilityDensityFunction ( ) : double
return double

LogProbabilityDensityFunction() public method

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

ProbabilityDensityFunction() public method

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

ProbabilityDensityFunction() public method

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

ToString() public method

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

WishartDistribution() public method

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