MultivariateNormalDistribution Methods 
The MultivariateNormalDistribution type exposes the following members.
Name  Description  

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.
(Overrides MultivariateContinuousDistributionComplementaryDistributionFunction(Double).)  
DistributionFunction 
Computes the cumulative distribution function for distributions
up to two dimensions. For more than two dimensions, this method
is not supported.
(Overrides MultivariateContinuousDistributionDistributionFunction(Double).)  
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(Int32, Int32) 
Generates a random vector of observations from the current distribution.
(Inherited from MultivariateContinuousDistribution.)  
Generate(Int32, Double) 
Generates a random vector of observations from the current distribution.
(Overrides MultivariateContinuousDistributionGenerate(Int32, Double).)  
Generate(Int32, Double, Double) 
Generates a random vector of observations from a distribution with the given parameters.
 
GetHashCode  Serves as the default hash function. (Inherited from Object.)  
GetType  Gets the Type of the current instance. (Inherited from Object.)  
LogProbabilityDensityFunction 
Gets the logprobability density function (pdf)
for this distribution evaluated at point x.
(Overrides MultivariateContinuousDistributionLogProbabilityDensityFunction(Double).)  
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.
(Overrides MultivariateContinuousDistributionProbabilityDensityFunction(Double).)  
ToIndependentNormalDistribution 
Converts this multivariate
normal distribution into a joint distribution
of independentnormal distributions.
 
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.

Name  Description  

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.)  
ToT  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.)  
ToT  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 Matrix.) 