R: Discrete Multivariate Distributions

DiscreteMVDistribution-class {distrEx} | R Documentation

## Discrete Multivariate Distributions

### Description

The class of discrete multivariate distributions.

### Objects from the Class

Objects can be created by calls of the form `new("DiscreteMVDistribution", ...)`. More frequently they are created via the generating function `DiscreteMVDistribution`.

### Slots

`img`

  Object of class `"rSpace"`. Image space of the distribution. Usually an object of class `"EuclideanSpace"`.

`param`

  Object of class `"OptionalParameter"`. Optional parameter of the multivariate distribution.

`r`

  Object of class `"function"`: generates (pseudo-)random numbers

`d`

  Object of class `"OptionalFunction"`: optional density function

`p`

  Object of class `"OptionalFunction"`: optional cumulative distribution function

`q`

  Object of class `"OptionalFunction"`: optional quantile function

`support`

  numeric matrix whose rows form the support of the distribution

`.finSupport`

  logical: (later on to be) used internally to check whether the true support is finite; the element in the 1st row and ith column indicates whether the ith marginal distribution has a finite left endpoint, and the element in the 2nd row and ith column if it is has a finite right endpoint); not yet further used.

`.withArith`

  logical: used internally to issue warnings as to interpretation of arithmetics

`.withSim`

  logical: used internally to issue warnings as to accuracy

`.logExact`

  logical: used internally to flag the case where there are explicit formulae for the log version of density, cdf, and quantile function

`.lowerExact`

  logical: used internally to flag the case where there are explicit formulae for the lower tail version of cdf and quantile function

### Extends

Class `"MultivariateDistribution"`, directly.
Class `"Distribution"`, by class `"MultivariateDistribution"`.

### Methods

support

  `signature(object = "DiscreteMVDistribution")`: accessor function for slot `support`.

### Author(s)

Matthias Kohl Matthias.Kohl@stamats.de

### See Also

`Distribution-class`, `MultivariateDistribution-class`, `DiscreteMVDistribution`, `E-methods`

### Examples

    (D1 <- new("MultivariateDistribution")) # Dirac measure in (0,0)
    r(D1)(5)

    (D2 <- DiscreteMVDistribution(supp = matrix(c(1:5, rep(3, 5)), ncol=2, byrow=TRUE)))
    support(D2)
    r(D2)(10)
    d(D2)(support(D2))
    p(D2)(lower = c(1,1), upper = c(3,3))
    q(D2)
    ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
    param(D2)
    img(D2)

    e1 <- E(D2) # expectation

[Package distrEx version 2.8.0 Index]