Pois-class: Class "Pois"
In distr: Object Oriented Implementation of Distributions

Pois-class

R Documentation

Class "Pois"

Description

The Poisson distribution has density

p(x) = \frac{\lambda^x e^{-\lambda}}{x!}

for x = 0, 1, 2, \ldots. The mean and variance are E(X) = Var(X) = \lambda.

C.f. rpois

Objects from the Class

Objects can be created by calls of the form Pois(lambda). This object is a Poisson distribution.

Slots

img: Object of class "Naturals": The space of the image of this distribution has got dimension 1 and the name "Natural Space".
param: Object of class "PoisParameter": the parameter of this distribution (lambda), declared at its instantiation
r: Object of class "function": generates random numbers (calls function rpois)
d: Object of class "function": density function (calls function dpois)
p: Object of class "function": cumulative function (calls function ppois)
q: Object of class "function": inverse of the cumulative function (calls function qpois). The quantile is defined as the smallest value x such that F(x) \ge p, where F is the distribution function.
support: Object of class "numeric": a (sorted) vector containing the support of the discrete density function
.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
Symmetry: object of class "DistributionSymmetry"; used internally to avoid unnecessary calculations.

Extends

Class "DiscreteDistribution", directly. Class "UnivariateDistribution", by class "DiscreteDistribution". Class "Distribution", by class "DiscreteDistribution".

Methods

+: signature(e1 = "Pois", e2 = "Pois"): For the Poisson distribution the exact convolution formula is implemented thereby improving the general numerical approximation.
initialize: signature(.Object = "Pois"): initialize method
lambda: signature(object = "Pois"): returns the slot lambda of the parameter of the distribution
lambda<-: signature(object = "Pois"): modifies the slot lambda of the parameter of the distribution

Note

Working with a computer, we use a finite interval as support which carries at least mass 1-getdistrOption("TruncQuantile").

Author(s)

Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de

Examples

P <- Pois(lambda = 1) # P is a Poisson distribution with lambda = 1.
r(P)(1) # one random number generated from this distribution, e.g. 1
d(P)(1) # Density of this distribution is 0.3678794 for x = 1.
p(P)(0.4) # Probability that x < 0.4 is 0.3678794.
q(P)(.1) # x = 0 is the smallest value x such that p(B)(x) >= 0.1.
## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
lambda(P) # lambda of this distribution is 1.
lambda(P) <- 2 # lambda of this distribution is now 2.
R <- Pois(lambda = 3) # R is a Poisson distribution with lambda = 2.
S <- P + R # R is a Poisson distribution with lambda = 5(=2+3).

distr documentation built on Nov. 6, 2024, 3:01 a.m.