| DiscreteDistribution-class {distr} | R Documentation |
The DiscreteDistribution-class is the mother-class of the classes Binom, Dirac,
Geom, Hyper, Nbinom and Poisson. Further discrete distributions can be defined either by
declaration of own random number generator, density and cumulative distribution and quantile functions, or as result of a
convolution of two discrete distributions or by application of a mathematical operator to a discrete distribution. An
additional way is, to specify only the random number generator. The function RtoDPQ.d then approximates the three
remaining slots d, p and q by random sampling.
Objects can be created by calls of the form new("DiscreteDistribution", r, d, p, q).
The result of this call is a discrete distribution.
img:"Reals": the space of the image of this distribution which has dimension 1
and the name "Real Space" param:"Parameter": the parameter of this distribution, having only the
slot name "Parameter of a discrete distribution" r:"function": generates random numbersd:"function": density/probability functionp:"function": cumulative distribution functionq:"function": quantile functionsupport:"numeric": a (sorted) vector containing the support of the discrete
density function
Class "UnivariateDistribution", directly.
Class "Distribution", by class "UnivariateDistribution".
signature(.Object = "DiscreteDistribution"): initialize method signature(x = "DiscreteDistribution"): application of a mathematical function, e.g. sin or
exp (does not work with log!), to this discrete distributionsignature(e1 = "DiscreteDistribution"): application of `-' to this discrete distributionsignature(e1 = "DiscreteDistribution", e2 = "numeric"): multiplication of this discrete distribution
by an object of class `numeric'signature(e1 = "DiscreteDistribution", e2 = "numeric"): division of this discrete distribution
by an object of class `numeric'signature(e1 = "DiscreteDistribution", e2 = "numeric"): addition of this discrete distribution
to an object of class `numeric'signature(e1 = "DiscreteDistribution", e2 = "numeric"): subtraction of an object of class `numeric'
from this discrete distribution signature(e1 = "numeric", e2 = "DiscreteDistribution"): multiplication of this discrete distribution
by an object of class `numeric'signature(e1 = "numeric", e2 = "DiscreteDistribution"): addition of this discrete distribution
to an object of class `numeric'signature(e1 = "numeric", e2 = "DiscreteDistribution"): subtraction of this discrete distribution
from an object of class `numeric'signature(e1 = "DiscreteDistribution", e2 = "DiscreteDistribution"): Convolution of two discrete
distributions. The slots p, d and q are approximated by grids.signature(e1 = "DiscreteDistribution", e2 = "DiscreteDistribution"): Convolution of two discrete
distributions. The slots p, d and q are approximated by grids.signature(object = "DiscreteDistribution"): returns the supportsignature(object = "DiscreteDistribution"): plots density, cumulative distribution and quantile
function Working with a computer, we use a finite interval as support which carries at least mass 1-TruncQuantile.
Thomas Stabla Thomas.Stabla@uni-bayreuth.de,
Florian Camphausen Florian.Camphausen@uni-bayreuth.de,
Peter Ruckdeschel Peter.Ruckdeschel@uni-bayreuth.de,
Matthias Kohl Matthias.Kohl@stamats.de
Parameter-class
UnivariateDistribution-class
Binom-class
Dirac-class
Geom-class
Hyper-class
Nbinom-class
Pois-class
AbscontDistribution-class
Reals-class
RtoDPQ.d
B = Binom(prob=0.1,size=10) # B is a Binomial distribution with prob=0.1 and size=10. P = Pois(lambda=1) # P is a Poisson distribution with lambda=1. D1 = B+1 # a new discrete distributions with exact slots d, p, q D2 = D1*3 # a new discrete distributions with exact slots d, p, q D3 = B+P # a new discrete distributions with approximated slots d, p, q D4 = D1+P # a new discrete distributions with approximated slots d, p, q support(D4) # the (approximated) support of this distribution is 1, 2, ..., 21 r(D4)(1) # one random number generated from this distribution, e.g. 4 d(D4)(1) # The (approximated) density for x=1 is 0.1282716. p(D4)(1) # The (approximated) probability that x<=1 is 0.1282716. q(D4)(.5) # The (approximated) 50 percent quantile is 3.