Namespaces

Types in MathNet.Numerics.Distributions

Type MatrixNormal

Namespace MathNet.Numerics.Distributions

Interfaces IDistribution

Multivariate Matrix-valued Normal distributions. The distribution is parameterized by a mean matrix (M), a covariance matrix for the rows (V) and a covariance matrix for the columns (K). If the dimension of M is d-by-m then V is d-by-d and K is m-by-m..

Constructors

Static Functions

Methods

Properties

Public Constructors

MatrixNormal(Matrix<T> m, Matrix<T> v, Matrix<T> k)

Initializes a new instance of the MatrixNormal class.
Parameters
Matrix<T> m

The mean of the matrix normal.

Matrix<T> v

The covariance matrix for the rows.

Matrix<T> k

The covariance matrix for the columns.

MatrixNormal(Matrix<T> m, Matrix<T> v, Matrix<T> k, Random randomSource)

Initializes a new instance of the MatrixNormal class.
Parameters
Matrix<T> m

The mean of the matrix normal.

Matrix<T> v

The covariance matrix for the rows.

Matrix<T> k

The covariance matrix for the columns.

Random randomSource

The random number generator which is used to draw random samples.

Public Static Functions

bool IsValidParameterSet(Matrix<T> m, Matrix<T> v, Matrix<T> k)

Tests whether the provided values are valid parameters for this distribution.
Parameters
Matrix<T> m

The mean of the matrix normal.

Matrix<T> v

The covariance matrix for the rows.

Matrix<T> k

The covariance matrix for the columns.

Matrix<T> Sample(Random rnd, Matrix<T> m, Matrix<T> v, Matrix<T> k)

Samples a matrix normal distributed random variable.
Parameters
Random rnd

The random number generator to use.

Matrix<T> m

The mean of the matrix normal.

Matrix<T> v

The covariance matrix for the rows.

Matrix<T> k

The covariance matrix for the columns.

Return
Matrix<T>

a sequence of samples from the distribution.

Public Methods

double Density(Matrix<T> x)

Evaluates the probability density function for the matrix normal distribution.
Parameters
Matrix<T> x

The matrix at which to evaluate the density at.

Return
double

the density at x

bool Equals(object obj)

int GetHashCode()

Type GetType()

Matrix<T> Sample()

Samples a matrix normal distributed random variable.
Return
Matrix<T>

A random number from this distribution.

string ToString()

Returns a String that represents this instance.
Return
string

A String that represents this instance.

Public Properties

Matrix<T> ColumnCovariance get;

Gets the column covariance. (K)
Value:

Matrix<T> Mean get;

Gets the mean. (M)
Value:

Random RandomSource get; set;

Gets or sets the random number generator which is used to draw random samples.

Matrix<T> RowCovariance get;

Gets the row covariance. (V)
Value: