﻿ MultivariateMixture(T) Methods   The MultivariateMixtureT generic type exposes the following members. Methods
NameDescription Clone
Creates a new object that is a copy of the current instance.
(Overrides DistributionBaseClone.) ComplementaryDistributionFunction
Gets the complementary cumulative distribution function (ccdf) for this distribution evaluated at point x. This function is also known as the Survival function.
(Inherited from MultivariateContinuousDistribution.) DistributionFunction(Double)
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.) DistributionFunction(Int32, Double)
Gets the cumulative distribution function (cdf) for one of the component distributions evaluated at point x. Equals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)  Estimate(Double, T)
Estimates a new mixture model from a given set of observations.  Estimate(Double, Double, T)
Estimates a new mixture model from a given set of observations.  Estimate(Double, Double, Double, T)
Estimates a new mixture model from a given set of observations. 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.
(Inherited from MultivariateContinuousDistribution.) Fit(Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.) Fit(Double, Double)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.) Fit(Double, Int32)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.) Fit(Double, Int32, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Inherited from MultivariateContinuousDistribution.) Fit(Double, Double, IFittingOptions)
Fits the underlying distribution to a given set of observations.
(Overrides MultivariateContinuousDistributionFit(Double, Double, IFittingOptions).) Fit(Double, Double, MixtureOptions)
Fits the underlying distribution to a given set of observations. Generate
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Double)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Int32)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Int32)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Double, Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Int32, Double)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Int32, Int32)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Int32, Random)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Int32, Random)
Generates a random observation from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Int32, Int32, Random)
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.) Generate(Int32, Double, Random)
Generates a random vector of observations from the current distribution.
(Overrides MultivariateContinuousDistributionGenerate(Int32, Double, Random).) 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.
(Inherited from MultivariateContinuousDistribution.) InnerDistributionFunction
Gets the cumulative distribution function (cdf) for this distribution evaluated at point x.
(Overrides MultivariateContinuousDistributionInnerDistributionFunction(Double).) InnerLogProbabilityDensityFunction
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
(Overrides MultivariateContinuousDistributionInnerLogProbabilityDensityFunction(Double).) InnerProbabilityDensityFunction
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Overrides MultivariateContinuousDistributionInnerProbabilityDensityFunction(Double).) LogLikelihood(Double)
Computes the log-likelihood of the distribution for a given set of observations. LogLikelihood(Double, Double)
Computes the log-likelihood of the distribution for a given set of observations. LogProbabilityDensityFunction(Double)
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.) LogProbabilityDensityFunction(Int32, Double)
Gets the log-probability density function (pdf) for one of the component distributions evaluated at point x. MemberwiseClone
Creates a shallow copy of the current Object.
(Inherited from Object.) ProbabilityDensityFunction(Double)
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.) ProbabilityDensityFunction(Int32, Double)
Gets the probability density function (pdf) for one of the component distributions 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.
(Overrides DistributionBaseToString(String, IFormatProvider).)
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.) To(Type)Overloaded.
Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.) ToTOverloaded.
Converts an object into another type, irrespective of whether the conversion can be done at compile time or not. This can be used to convert generic types to numeric types during runtime.
(Defined by ExtensionMethods.)
Top See Also