Class "Exp"
The exponential distribution with rate λ has density
f(x) = lambda e^(- lambda x)
for x ≥ 0.
C.f. rexp
Objects can be created by calls of the form Exp(rate).
This object is an exponential distribution.
imgObject of class "Reals":
The space of the image of this distribution has got dimension 1
and the name "Real Space".
paramObject of class "ExpParameter":
the parameter of this distribution (rate), declared at its instantiation
rObject of class "function":
generates random numbers (calls function rexp)
dObject of class "function":
density function (calls function dexp)
pObject of class "function":
cumulative function (calls function pexp)
qObject of class "function":
inverse of the cumulative function (calls function qexp)
.withArithlogical: used internally to issue warnings as to interpretation of arithmetics
.withSimlogical: used internally to issue warnings as to accuracy
.logExactlogical: used internally to flag the case where there are explicit formulae for the log version of density, cdf, and quantile function
.lowerExactlogical: used internally to flag the case where there are explicit formulae for the lower tail version of cdf and quantile function
Symmetryobject of class "DistributionSymmetry";
used internally to avoid unnecessary calculations.
Class "ExpOrGammaOrChisq", directly.
Class "AbscontDistribution", by class "ExpOrGammaOrChisq".
Class "UnivariateDistribution", by class "AbscontDistribution".
Class "Distribution", by class "AbscontDistribution".
By means of setIs, R “knows” that a distribution object obj of class "Exp" also is
a Gamma distribution with parameters shape = 1, scale = 1/rate(obj) and a Weibull distribution with
parameters shape = 1, scale = 1/rate(obj)
signature(.Object = "Exp"):
initialize method
signature(object = "Exp"):
returns the slot rate of the parameter of the distribution
signature(object = "Exp"):
modifies the slot rate of the parameter of the distribution
signature(e1 = "Exp", e2 = "numeric"):
For the exponential distribution we use its closedness under positive scaling transformations.
Thomas Stabla statho3@web.de,
Florian Camphausen fcampi@gmx.de,
Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de,
Matthias Kohl Matthias.Kohl@stamats.de
E <- Exp(rate = 1) # E is a exp distribution with rate = 1. r(E)(1) # one random number generated from this distribution, e.g. 0.4190765 d(E)(1) # Density of this distribution is 0.3678794 for x = 1. p(E)(1) # Probability that x < 1 is 0.6321206. q(E)(.1) # Probability that x < 0.1053605 is 0.1. ## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.) rate(E) # rate of this distribution is 1. rate(E) <- 2 # rate of this distribution is now 2. is(E, "Gammad") # yes as(E,"Gammad") is(E, "Weibull") E+E+E ### a Gammad -distribution 2*E+Gammad(scale=1)
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