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See:
Description
| Class Summary | |
|---|---|
| BiNormalDist | Extends the class ContinuousDistribution2Dim for the bivariate
normal distribution. |
| BiNormalDonnellyDist | Extends the class BiNormalDist for the bivariate
normal distribution
using a translation of Donnelly's FORTRAN code. |
| BiNormalGenzDist | Extends the class BiNormalDist for the bivariate
normal distribution
using Genz's algorithm as described in. |
| BiStudentDist | Extends the class ContinuousDistribution2Dim for the standard bivariate Student's t distribution. |
| ContinuousDistribution2Dim | Classes implementing 2-dimensional continuous distributions should inherit from this class. |
| ContinuousDistributionMulti | ContinuousDistributionMulti |
| DirichletDist | Implements the abstract class ContinuousDistributionMulti for the
Dirichlet distribution with parameters
(α1,...,αd),
αi > 0. |
| DiscreteDistributionIntMulti | Classes implementing multi-dimensional discrete distributions over the integers should inherit from this class. |
| MultinomialDist | MultinomialDist |
| MultiNormalDist | Implements the abstract class ContinuousDistributionMulti for the
multinormal distribution with mean vector μ and covariance
matrix
Σ. |
| NegativeMultinomialDist | Implements the class DiscreteDistributionIntMulti for the
negative multinomial distribution with parameters n > 0 and
(
p1,…, pd) such that all 0 < pi < 1 and
∑i=1dpi < 1. |
This package contains Java classes providing methods to compute mass, density, distribution and complementary distribution functions for some multi-dimensional discrete and continuous probability distributions. It does not generate random numbers for multivariate distributions; for that, see the package umontreal.iro.lecuyerrandvarmulti.
We recall that the distribution function of a continuous random
vector
X = {x1, x2,…, xd} with density
f (x1, x2,…, xd) over the
d-dimensional space Rd is
We define
, the complementary distribution function
of X, as
(x1, x2,…, xd) = P[X1≥x1, X2≥x2,…, Xd≥xd].
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SSJ V. labo. |
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