DirichletDistribution Constructor

public DirichletDistribution(
	Matrix<double> data
)

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

public:
DirichletDistribution(
	Matrix<double>^ data
)

new : 
        data : Matrix<float> -> DirichletDistribution

Parameters

data  Matrix<Double>

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

Return Value

Use this constructor to create a DirichletDistribution whose parameters are estimated from data. Fitting uses the sample means and the trace of the unbiased sample covariance. Parameter estimates themselves are not generally unbiased. At least two observations and two variables are required. Each row must lie strictly inside the simplex and sum to one within the simplex tolerance.

public DirichletDistribution(
	Vector<double> parameters
)

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

public:
DirichletDistribution(
	Vector<double>^ parameters
)

new : 
        parameters : Vector<float> -> DirichletDistribution

Parameters

parameters  Vector<Double>

The nonempty vector of positive finite shape parameters, whose sum must also be finite. Its values are copied.

public DirichletDistribution(
	Vector<double>[] variables
)

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

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

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

Parameters

variables  Vector<Double>[]

An array of vectors.

Return Value

Use this constructor to create a DirichletDistribution whose parameters are estimated from variables. Each vector is one variable and must have the same observation count. The fitting method and validity rules match DirichletDistribution(Matrix<Double>).

Reference