DiscreteMVDistribution-class | R Documentation |
The class of discrete multivariate distributions.
Objects can be created by calls of the form new("DiscreteMVDistribution", ...)
.
More frequently they are created via the generating function
DiscreteMVDistribution
.
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
Class "MultivariateDistribution"
, directly.
Class "Distribution"
, by class "MultivariateDistribution"
.
signature(object = "DiscreteMVDistribution")
:
accessor function for slot support
.
Matthias Kohl Matthias.Kohl@stamats.de
Distribution-class
, MultivariateDistribution-class
,
DiscreteMVDistribution
, E-methods
(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
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