AbscontDistribution-class
Class "AbscontDistribution"
The AbscontDistribution-class is the mother-class of the classes Beta, Cauchy,
Chisq, Exp, F, Gammad, Lnorm, Logis, Norm, T, Unif and
Weibull. Further absolutely continuous distributions can be defined either by declaration of
own random number generator, density, cumulative distribution and quantile functions, or as result of a
convolution of two absolutely continuous distributions or by application of a mathematical operator to an absolutely
continuous distribution.
- Keywords
- distribution
Objects from the Class
Objects can be created by calls of the form new("AbscontDistribution", r, d, p, q).
More comfortably, you may use the generating function AbscontDistribution.
The result of these calls is an absolutely continuous distribution.
Extends
Class "UnivariateDistribution", directly.
Class "Distribution", by class "UnivariateDistribution".
Internal virtual superclass "AcDcLcDistribution"
As many operations should be valid no matter whether the operands
are of class "AbscontDistribution",
"DiscreteDistribution", or "UnivarLebDecDistribution",
there is a class union of these classes called "AcDcLcDistribution";
in partiucalar methods for "*", "/",
"^" (see operators-methods) and methods
Minimum, Maximum, Truncate, and
Huberize, and convpow are defined for this
class union.
concept
- absolutely continuous distribution
- S4 distribution class
See Also
AbscontDistribution
Parameter-class
UnivariateDistribution-class
Beta-class
Cauchy-class
Chisq-class
Exp-class
Fd-class
Gammad-class
Lnorm-class
Logis-class
Norm-class
Td-class
Unif-class
Weibull-class
DiscreteDistribution-class
Reals-class
RtoDPQ
Examples
N <- Norm() # N is a normal distribution with mean=0 and sd=1.
E <- Exp() # E is an exponential distribution with rate=1.
A1 <- E+1 # a new absolutely continuous distributions with exact slots d, p, q
A2 <- A1*3 # a new absolutely continuous distributions with exact slots d, p, q
A3 <- N*0.9 + E*0.1 # a new absolutely continuous distribution with approximated slots d, p, q
r(A3)(1) # one random number generated from this distribution, e.g. -0.7150937
d(A3)(0) # The (approximated) density for x=0 is 0.4379882.
p(A3)(0) # The (approximated) probability that x <= 0 is 0.4562021.
q(A3)(.1) # The (approximated) 10 percent quantile is 0.1.