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  • Extreme.Statistics.Distributions
    • BernoulliDistribution Class
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  • MultivariateNormalDistribution Class
    • MultivariateNormalDistribution Constructors
    • MultivariateNormalDistribution Properties
    • Methods
MultivariateNormalDistribution ClassExtreme Optimization Numerical Libraries for .NET Professional
Represents a multivariate normal distribution.
Inheritance Hierarchy
SystemObject
  Extreme.Statistics.DistributionsMultivariateContinuousDistribution
    Extreme.Statistics.DistributionsMultivariateNormalDistribution

Namespace: Extreme.Statistics.Distributions
Assembly: Extreme.Numerics.Net40 (in Extreme.Numerics.Net40.dll) Version: 6.0.16073.0 (6.0.16312.0)
Syntax
C#
VB
C++
F#
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[SerializableAttribute]
public sealed class MultivariateNormalDistribution : MultivariateContinuousDistribution
<SerializableAttribute>
Public NotInheritable Class MultivariateNormalDistribution
	Inherits MultivariateContinuousDistribution
[SerializableAttribute]
public ref class MultivariateNormalDistribution sealed : public MultivariateContinuousDistribution
[<SealedAttribute>]
[<SerializableAttribute>]
type MultivariateNormalDistribution =  
    class
        inherit MultivariateContinuousDistribution
    end

The MultivariateNormalDistribution type exposes the following members.

Constructors
  NameDescription
Public methodMultivariateNormalDistribution(Int32)
Constructs a new MultivariateNormalDistribution with mean equal to zero and standard deviation equal to 1.
Public methodMultivariateNormalDistribution(MatrixDouble)
Estimates the parameters of the distribution of a set of observations assuming it follows a multivariate normal distribution.
Public methodMultivariateNormalDistribution(Matrix)
Estimates the parameters of the distribution of a set of observations assuming it follows a multivariate normal distribution.
Public methodMultivariateNormalDistribution(NumericalVariable)
Estimates the parameters of the distribution of a variable assuming it follows a normal distribution.
Public methodMultivariateNormalDistribution(VectorDouble)
Constructs a new MultivariateNormalDistribution with specified mean and standard deviation equal to 1.
Public methodMultivariateNormalDistribution(VectorDouble)
Estimates the parameters of the distribution of a variable assuming it follows a normal distribution.
Public methodMultivariateNormalDistribution(Vector)
Constructs a new MultivariateNormalDistribution with specified mean and standard deviation equal to 1.
Public methodMultivariateNormalDistribution(VectorDouble, MatrixDouble)
Constructs a new MultivariateNormalDistribution with specified mean and standard deviation.
Public methodMultivariateNormalDistribution(Vector, SymmetricMatrix)
Constructs a new MultivariateNormalDistribution with specified mean and standard deviation.
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Properties
  NameDescription
Public propertyOrder
Gets the number of dimensions of the distribution.
(Inherited from MultivariateContinuousDistribution.)
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Methods
  NameDescription
Public methodStatic memberCreateStandard
Represents the standard MultivariateNormalDistribution.
Public methodDistributionFunction(VectorDouble)
Returns the cumulative distribution function (CDF) of this distribution for the specified value.
Public methodDistributionFunction(Vector)
Returns the cumulative distribution function (CDF) of this distribution for the specified value.
Public methodEquals
Determines whether the specified Object is equal to the current Object.
(Inherited from Object.)
Public methodFillSample(Random, VectorDouble)
Fills a vector with a random sample from the distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodFillSample(Random, Double)
Fills a Double array with random numbers.
(Inherited from MultivariateContinuousDistribution.)
Public methodFillSample(Random, Vector)
Fills a vector with a random sample from the distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodFillSamples(Random, MatrixDouble)
Fills the rows of a matrix with random samples from the distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodFillSamples(Random, Matrix)
Fills the rows of a matrix with random samples from the distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGetHashCode
Serves as a hash function for a particular type.
(Inherited from Object.)
Public methodGetMeans
Returns the mean or expectation value of the distribution.
(Overrides MultivariateContinuousDistributionGetMeans.)
Public methodGetRandomVariate Obsolete.
Returns a random sample from the distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGetRandomVariates
Returns a matrix with random samples from the distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodGetType
Gets the Type of the current instance.
(Inherited from Object.)
Public methodGetVarianceCovarianceMatrix
Returns the variance of the distribution.
(Overrides MultivariateContinuousDistributionGetVarianceCovarianceMatrix.)
Public methodLogProbabilityDensityFunction(VectorDouble)
Returns the natural logarithm of the probability density function (PDF) of this distribution for the specified value.
(Overrides MultivariateContinuousDistributionLogProbabilityDensityFunction(VectorDouble).)
Public methodLogProbabilityDensityFunction(Vector)
Returns the natural logarithm of the probability density function (PDF) of this distribution for the specified value.
(Overrides MultivariateContinuousDistributionLogProbabilityDensityFunction(Vector).)
Public methodProbabilityDensityFunction(VectorDouble)
Returns the value of the probability density function (PDF) of this distribution for the specified value.
(Inherited from MultivariateContinuousDistribution.)
Public methodProbabilityDensityFunction(Vector)
Returns the value of the probability density function (PDF) of this distribution for the specified value.
(Inherited from MultivariateContinuousDistribution.)
Public methodSample(Random)
Returns a random sample from the distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodSample(Random, Int32)
Returns a matrix with random samples from the distribution.
(Inherited from MultivariateContinuousDistribution.)
Public methodToString
Returns a string that represents the current object.
(Inherited from Object.)
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Remarks

The multivariate normal distribution is a generalization of the normal distribution. The mean of the multivariate distribution is a vector. The multivariate equivalent of the variance is the variance-covariance matrix, which must be positive semi-definite.

Version Information

Numerical Libraries

Supported in: 6.0, 5.x, 4.x
See Also

Reference

Extreme.Statistics.Distributions Namespace

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