Objects from the Class
Objects can be created by calls of the form Exp(rate).
This object is an exponential distribution.Slots
img- Object of class
"Reals":
The space of the image of this distribution has got dimension 1
and the name "Real Space". param- Object of class
"ExpParameter":
the parameter of this distribution (rate), declared at its instantiation r- Object of class
"function":
generates random numbers (calls function rexp) d- Object of class
"function":
density function (calls function dexp) p- Object of class
"function":
cumulative function (calls function pexp) q- Object of class
"function":
inverse of the cumulative function (calls function qexp) .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 "ExpOrGammaOrChisq", directly.
Class "AbscontDistribution", by class "ExpOrGammaOrChisq".
Class "UnivariateDistribution", by class "AbscontDistribution".
Class "Distribution", by class "AbscontDistribution".Is-Relations
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)Methods
- initialize
signature(.Object = "Exp"):
initialize method - rate
signature(object = "Exp"):
returns the slot rate of the parameter of the distribution - rate<-
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.