Generates an object of class  "DiscreteDistribution"
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())numeric vector which forms the support of the discrete distribution.
vector of probability weights for the
    elements of supp.
normally not set by the user, but if determining the entries supp, prob
                    distributional arithmetics was involved, you may set this to TRUE.
normally not set by the user, but if determining the entries supp, prob
                  simulations were involved, you may set this to TRUE.
normally not set by the user: whether the lower.tail=FALSE
                     part is calculated exactly, avoing a ``1-.''.
normally not set by the user: whether in determining slots d,p,q,
         we make particular use of a logarithmic representation to enhance accuracy.
controls whether in generating a new discrete 
     distribution, support points closer together than .DistrResolution are
     collapsed.
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)
minimal spacing between two mass points in a discrete distribution
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).
Object of class "DiscreteDistribution"
If prob is missing, all elements in supp
  are equally weighted.
Typical usages are
    DiscreteDistribution(supp, prob)
    DiscreteDistribution(supp)
  DiscreteDistribution-class
AbscontDistribution-class
RtoDPQ.d
# NOT RUN {
# 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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