DiscreteDistribution: Generating function "DiscreteDistribution"

Description

Generates an object of class "DiscreteDistribution"

Usage

DiscreteDistribution(supp, prob, .withArith=FALSE, .withSim=FALSE, 
                       .lowerExact = TRUE, .logExact = FALSE,
             .DistrCollapse = getdistrOption("DistrCollapse"),
             .DistrCollapse.Unique.Warn = 
                  getdistrOption("DistrCollapse.Unique.Warn"),
             .DistrResolution = getdistrOption("DistrResolution"),
             Symmetry = NoSymmetry())

Value

Object of class "DiscreteDistribution"

Arguments

supp: numeric vector which forms the support of the discrete distribution.
prob: vector of probability weights for the elements of supp.
.withArith: normally not set by the user, but if determining the entries supp, prob distributional arithmetics was involved, you may set this to TRUE.
.withSim: normally not set by the user, but if determining the entries supp, prob simulations were involved, you may set this to TRUE.
.lowerExact: normally not set by the user: whether the lower.tail=FALSE part is calculated exactly, avoing a ``1-.''.
.logExact: normally not set by the user: whether in determining slots d,p,q, we make particular use of a logarithmic representation to enhance accuracy.
.DistrCollapse: controls whether in generating a new discrete distribution, support points closer together than .DistrResolution are collapsed.
.DistrCollapse.Unique.Warn: controls whether there is a warning whenever collapsing occurs or when two points are collapsed by a call to unique() (default behaviour if .DistrCollapse is FALSE)
.DistrResolution: minimal spacing between two mass points in a discrete distribution
Symmetry: you may help R in calculations if you tell it whether the distribution is non-symmetric (default) or symmetric with respect to a center; in this case use Symmetry=SphericalSymmetry(center).

Author

Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de

Details

If prob is missing, all elements in supp are equally weighted.

Typical usages are


    DiscreteDistribution(supp, prob)
    DiscreteDistribution(supp)

Examples

Run this code

# Dirac-measure at 0
D1 <- DiscreteDistribution(supp = 0)
D1
# simple discrete distribution
D2 <- DiscreteDistribution(supp = c(1:5), prob = c(0.1, 0.2, 0.3, 0.2, 0.2))
D2

plot(D2)

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