DiscreteDistributionIntMulti Class Reference

Classes implementing multi-dimensional discrete distributions over the integers should inherit from this class. More...

Inheritance diagram for DiscreteDistributionIntMulti:

Public Member Functions
abstract double	prob (int[] x)
	Returns the probability mass function \(p(x_1, x_2, …, x_d)\), which should be a real number in \([0,1]\). More...
double	cdf (int x[])
	Computes the cumulative probability function \(F\) of the distribution evaluated at x, assuming the lowest values start at 0, i.e. 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 multi-dimensional discrete distributions over the integers should inherit from this class.

It specifies the signature of methods for computing the mass function (or probability) \(p(x_1, x_2, …, x_d) = P[X_1 = x_1, X_2 = x_2, …, X_d = x_d]\) and the cumulative probabilities for a random vector \(X\) with a discrete distribution over the integers.

Member Function Documentation

cdf()

double cdf

(

int

x[]

)

Computes the cumulative probability function \(F\) of the distribution evaluated at x, assuming the lowest values start at 0, i.e.

computes

\[ F (x_1, x_2, …, x_d) = \sum_{s_1=0}^{x_1} \sum_{s_2=0}^{x_2} \cdots\sum_{s_d=0}^{x_d} p(s_1, s_2, …, s_d). \]

Uses the naive implementation, is very inefficient and may underflows.

prob()

abstract double prob ( int []  x )

abstract

Returns the probability mass function \(p(x_1, x_2, …, x_d)\), which should be a real number in \([0,1]\).

Parameters

x	value at which the mass function must be evaluated

Returns

the mass function evaluated at x

---

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

• DiscreteDistributionIntMulti.java