ContinuousDistributionMulti Class Reference

Classes implementing continuous multi-dimensional distributions should inherit from this class. More...

Inheritance diagram for ContinuousDistributionMulti:

Public Member Functions
abstract double	density (double[] x)
	Returns \(f(x_1, x_2, …, x_d)\), the probability density of \(X\) evaluated at the point \(x\), where \(x = \{x_1, x_2, …, x_d\}\). More...
int	getDimension ()
	Returns the dimension \(d\) of the distribution.
abstract double []	getMean ()
	Returns the mean vector of the distribution, defined as \(\mu_i = E[X_i]\).
abstract double [][]	getCovariance ()
	Returns the variance-covariance matrix of the distribution, defined as \(\sigma_{ij} = E[(X_i - \mu_i)(X_j - \mu_j)]\).
abstract double [][]	getCorrelation ()
	Returns the correlation matrix of the distribution, defined as \(\rho_{ij} = \sigma_{ij}/\sqrt{\sigma_{ii}\sigma_{jj}}\).

Protected Attributes
int	dimension

Detailed Description

Classes implementing continuous multi-dimensional distributions should inherit from this class.

Such distributions are characterized by a density function \(f(x_1, x_2, …, x_d)\); thus the signature of a density method is supplied here. All array indices start at 0.

Member Function Documentation

density()

abstract double density ( double []  x )

abstract

Returns \(f(x_1, x_2, …, x_d)\), the probability density of \(X\) evaluated at the point \(x\), where \(x = \{x_1, x_2, …, x_d\}\).

The convention is that \(\mathtt{x[i-1]} = x_i\).

Parameters

x	value at which the density is evaluated

Returns

density function evaluated at x

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The documentation for this class was generated from the following file:

• ContinuousDistributionMulti.java