[SerializableAttribute]
public abstract class MultivariateContinuousDistribution

<SerializableAttribute>
Public MustInherit Class MultivariateContinuousDistribution

[SerializableAttribute]
public ref class MultivariateContinuousDistribution abstract

[<AbstractClassAttribute>]
[<SerializableAttribute>]
type MultivariateContinuousDistribution =  class end

The MultivariateContinuousDistribution type exposes the following members.

	Name	Description
	MultivariateContinuousDistribution	Constructs a new MultivariateContinuousDistribution object.

	Name	Description
	Order	Gets the number of dimensions of the distribution.

	Name	Description
	Equals	Determines whether the specified Object is equal to the current Object. (Inherited from Object.)
	FillSample(Random, VectorDouble)	Fills a vector with a random sample from the distribution.
	FillSample(Random, Double)	Fills a Double array with random numbers.
	FillSample(Random, Vector)	Fills a vector with a random sample from the distribution.
	FillSampleCore(Random, VectorDouble)	Fills a vector with a random sample from the distribution.
	FillSampleCore(Random, Vector)	Fills a vector with a random sample from the distribution.
	FillSamples(Random, MatrixDouble)	Fills the rows of a matrix with random samples from the distribution.
	FillSamples(Random, Matrix)	Fills the rows of a matrix with random samples from the distribution.
	Finalize	Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection. (Inherited from Object.)
	GetHashCode	Serves as a hash function for a particular type. (Inherited from Object.)
	GetMeans	Returns the mean or expectation value of the distribution.
	GetRandomVariate	Obsolete. Returns a random sample from the distribution.
	GetRandomVariates	Returns a matrix with random samples from the distribution.
	GetType	Gets the Type of the current instance. (Inherited from Object.)
	GetVarianceCovarianceMatrix	Returns the variance of the distribution.
	LogProbabilityDensityFunction(VectorDouble)	Returns the natural logarithm of the probability density function (PDF) of this distribution for the specified value.
	LogProbabilityDensityFunction(Vector)	Returns the natural logarithm of the probability density function (PDF) of this distribution for the specified value.
	MemberwiseClone	Creates a shallow copy of the current Object. (Inherited from Object.)
	ProbabilityDensityFunction(VectorDouble)	Returns the value of the probability density function (PDF) of this distribution for the specified value.
	ProbabilityDensityFunction(Vector)	Returns the value of the probability density function (PDF) of this distribution for the specified value.
	Sample(Random)	Returns a random sample from the distribution.
	Sample(Random, Int32)	Returns a matrix with random samples from the distribution.
	ToString	Returns a string that represents the current object. (Inherited from Object.)

The distribution of a variable is a description of the relative numbers of times each possible outcome will occur in a number of trials. The function describing the distribution is called the probability function, and the function describing the cumulative probability that a given value or any value smaller than it will occur is called the distribution function.

A continuous probability distribution is a statistical distribution whose variables can take on any value within a certain interval. This interval may be infinite.

This library contains classes for the most common multivariate continuous distributions. They are listed in the table below:

MultivariateContinuousDistribution is an abstract base class that cannot be instantiated. To create a continuous distribution of a specific type, instantiate a class derived from MultivariateContinuousDistribution.

Notes to inheritors: When you inherit from MultivariateContinuousDistribution, you must override the following members: LogProbabilityDensityFunction(VectorDouble), FillSampleCore(Random, VectorDouble), GetMeans, and GetVarianceCovarianceMatrix.

Numerical Libraries

Reference