﻿ MultivariateNormalDistribution Methods

# MultivariateNormalDistribution Methods

The MultivariateNormalDistribution type exposes the following members.

Methods
NameDescription
Bivariate
Creates a new bivariate Normal distribution.
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
Gets the probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.)
Equals
Determines whether the specified object is equal to the current object.
(Inherited from Object.)
Estimate(Double)
Estimates a new Normal distribution from a given set of observations.
Estimate(Double, NormalOptions)
Estimates a new Normal distribution from a given set of observations.
Estimate(Double, Double)
Estimates a new Normal distribution from a given set of observations.
Estimate(Double, Double, NormalOptions)
Estimates a new Normal distribution 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, NormalOptions)
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, Double)
Generates a random vector of observations from a distribution with the given parameters.
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.
(Overrides MultivariateContinuousDistributionInnerComplementaryDistributionFunction(Double).)
InnerDistributionFunction
Computes the cumulative distribution function for distributions up to two dimensions. For more than two dimensions, this method is not supported.
(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).)
LogProbabilityDensityFunction
Gets the log-probability density function (pdf) for this distribution evaluated at point x.
(Inherited from MultivariateContinuousDistribution.)
Mahalanobis
Gets the Mahalanobis distance between a sample and this distribution.
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.
(Inherited from MultivariateContinuousDistribution.)
ToIndependentNormalDistribution
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).)
Univariate
Creates a new univariate Normal distribution.
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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.)