﻿ MultivariateContinuousDistribution Methods

# MultivariateContinuousDistribution Methods

The MultivariateContinuousDistribution type exposes the following members.

Methods
NameDescription
Clone
Creates a new object that is a copy of the current instance.
(Inherited from DistributionBase.)
ComplementaryDistributionFunction
Gets the complementary cumulative distribution function (ccdf) for this distribution evaluated at point x. This function is also known as the Survival function.
DistributionFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
Equals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Finalize
Allows an object to try to free resources and perform other cleanup operations before it is reclaimed by garbage collection.
(Inherited from Object.)
Fit(Double)
Fits the underlying distribution to a given set of observations.
Fit(Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
Fit(Double, Double)
Fits the underlying distribution to a given set of observations.
Fit(Double, Int32)
Fits the underlying distribution to a given set of observations.
Fit(Double, Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
Fit(Double, Int32, IFittingOptions)
Fits the underlying distribution to a given set of observations.
Generate
Generates a random observation from the current distribution.
Generate(Double)
Generates a random observation from the current distribution.
Generate(Int32)
Generates a random vector of observations from the current distribution.
Generate(Int32)
Generates a random observation from the current distribution.
Generate(Random)
Generates a random observation from the current distribution.
Generate(Double, Random)
Generates a random observation from the current distribution.
Generate(Int32, Double)
Generates a random vector of observations from the current distribution.
Generate(Int32, Int32)
Generates a random vector of observations from the current distribution.
Generate(Int32, Random)
Generates a random vector of observations from the current distribution.
Generate(Int32, Random)
Generates a random observation from the current distribution.
Generate(Int32, Double, Random)
Generates a random vector of observations from the current distribution.
Generate(Int32, Int32, Random)
Generates a random vector of observations from the current distribution.
GetHashCode
Serves as the default hash function.
(Inherited from Object.)
GetType
Gets the Type of the current instance.
(Inherited from Object.)
InnerComplementaryDistributionFunction
Gets the complementary cumulative distribution function (ccdf) for this distribution evaluated at point x. This function is also known as the Survival function.
InnerDistributionFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
InnerLogProbabilityDensityFunction
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
InnerProbabilityDensityFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
LogProbabilityDensityFunction
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
MemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.)
ProbabilityDensityFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
ToString
Returns a String that represents this instance.
(Inherited from DistributionBase.)
ToString(IFormatProvider)
Returns a String that represents this instance.
(Inherited from DistributionBase.)
ToString(String)
Returns a String that represents this instance.
(Inherited from DistributionBase.)
ToString(String, IFormatProvider)
Returns a String that represents this instance.
(Inherited from DistributionBase.)
Top
Extension Methods
NameDescription
HasMethod
Checks whether an object implements a method with the given name.
(Defined by ExtensionMethods.)
IsEqual
Compares two objects for equality, performing an elementwise comparison if the elements are vectors or matrices.
(Defined by Matrix.)