MultivariateNormalDistribution Constructor

Definition

Namespace: Numerics.NET.Statistics.Distributions
Assembly: Numerics.NET (in Numerics.NET.dll) Version: 9.0.2

Overload List

MultivariateNormalDistribution(Int32)	Constructs a new MultivariateNormalDistribution with mean equal to zero and standard deviation equal to 1.
MultivariateNormalDistribution(Matrix<Double>)	Estimates the parameters of the distribution of a set of observations assuming it follows a multivariate normal distribution.
MultivariateNormalDistribution(Vector<Double>)	Constructs a new MultivariateNormalDistribution with specified mean and standard deviation equal to 1.
MultivariateNormalDistribution(Vector<Double>[])	Estimates the parameters of the distribution of a variable assuming it follows a normal distribution.
MultivariateNormalDistribution(Vector<Double>, Matrix<Double>)	Constructs a new MultivariateNormalDistribution with specified mean and standard deviation.

MultivariateNormalDistribution(Int32)

Constructs a new MultivariateNormalDistribution with mean equal to zero and standard deviation equal to 1.

public MultivariateNormalDistribution(
	int order
)

Visual Basic

Public Sub New ( 
	order As Integer
)

C++/CLI

public:
MultivariateNormalDistribution(
	int order
)

new : 
        order : int -> MultivariateNormalDistribution

Parameters

order Int32

Remarks

This constructor creates a standard normal distribution, with mean zero and standard deviation equal to one.

MultivariateNormalDistribution(Matrix<Double>)

Estimates the parameters of the distribution of a set of observations assuming it follows a multivariate normal distribution.

public MultivariateNormalDistribution(
	Matrix<double> data
)

Visual Basic

Public Sub New ( 
	data As Matrix(Of Double)
)

C++/CLI

public:
MultivariateNormalDistribution(
	Matrix<double>^ data
)

new : 
        data : Matrix<float> -> MultivariateNormalDistribution

Parameters

data Matrix<Double>: A real Matrix<T> whose rows contain the observations.

Return Value

The MultivariateNormalDistribution that best matches the distribution of the rows of data.

Remarks

Use this constructor to create a MultivariateNormalDistribution whose parameters are estimated from data. This constructor uses an unbiased estimator.

Exceptions

ArgumentNullException

data is null.

MultivariateNormalDistribution(Vector<Double>)

Constructs a new MultivariateNormalDistribution with specified mean and standard deviation equal to 1.

public MultivariateNormalDistribution(
	Vector<double> mean
)

Visual Basic

Public Sub New ( 
	mean As Vector(Of Double)
)

C++/CLI

public:
MultivariateNormalDistribution(
	Vector<double>^ mean
)

new : 
        mean : Vector<float> -> MultivariateNormalDistribution

Parameters

mean Vector<Double>: The mean of the distribution.

MultivariateNormalDistribution(Vector<Double>[])

Estimates the parameters of the distribution of a variable assuming it follows a normal distribution.

public MultivariateNormalDistribution(
	Vector<double>[] variables
)

Visual Basic

Public Sub New ( 
	variables As Vector(Of Double)()
)

C++/CLI

public:
MultivariateNormalDistribution(
	array<Vector<double>^>^ variables
)

new : 
        variables : Vector<float>[] -> MultivariateNormalDistribution

Parameters

variables Vector<Double>[]: An array of vectors.

Return Value

The MultivariateNormalDistribution that best matches the distribution of variables.

Remarks

Use this constructor to create a MultivariateNormalDistribution whose parameters are estimated from variables. This constructor uses an unbiased estimator.

Exceptions

ArgumentNullException

variables is null.

MultivariateNormalDistribution(Vector<Double>, Matrix<Double>)

Constructs a new MultivariateNormalDistribution with specified mean and standard deviation.

public MultivariateNormalDistribution(
	Vector<double> mean,
	Matrix<double> covarianceMatrix
)

Visual Basic

Public Sub New ( 
	mean As Vector(Of Double),
	covarianceMatrix As Matrix(Of Double)
)

C++/CLI

public:
MultivariateNormalDistribution(
	Vector<double>^ mean, 
	Matrix<double>^ covarianceMatrix
)

new : 
        mean : Vector<float> * 
        covarianceMatrix : Matrix<float> -> MultivariateNormalDistribution

Parameters

mean Vector<Double>: The mean of the distribution.
covarianceMatrix Matrix<Double>: A SymmetricMatrix<T> that specifies the variance-covariance matrix of the distribution.

Remarks

The standard deviation must be greater than zero.

Exceptions

ArgumentNullException

mean is null.

-or-

covarianceMatrix is null.

DimensionMismatchException

The size of covarianceMatrix does not equal the length of mean.

MultivariateNormalDistribution Constructor

Definition

Overload List

MultivariateNormalDistribution(Int32)

Parameters

Remarks

MultivariateNormalDistribution(Matrix<Double>)

Parameters

Return Value

Remarks

Exceptions

MultivariateNormalDistribution(Vector<Double>)

Parameters

MultivariateNormalDistribution(Vector<Double>[])

Parameters

Return Value

Remarks

Exceptions

MultivariateNormalDistribution(Vector<Double>, Matrix<Double>)

Parameters

Remarks

Exceptions

See Also

Reference