Class "MultivarMixingDistribution"

Share:

Description

MultivarMixingDistribution-class is a class to formalize multivariate mixing distributions; it is a subclass to class MultivariateDistribution.

Objects from the Class

Objects can be created by calls of the form new("MultivarMixingDistribution", ...). More frequently they are created via the generating function MultivarMixingDistribution.

Slots

mixCoeff

Object of class "numeric": a vector of probabilities for the mixing components.

mixDistr

Object of class "MultivarDistrList": a list of multivariate distributions containing the mixing components; must be of same length as mixCoeff.

img

Object of class "Reals": the space of the image of this distribution which has dimension 1 and the name "Real Space"

param

Object of class "Parameter": the parameter of this distribution, having only the slot name "Parameter of a discrete distribution"

r

Object of class "function": generates random numbers

d

fixed to NULL

p

Object of class "OptionalFunction": if non-null cumulative distribution function

q

Object of class "OptionalFunction": if non-null quantile 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 "MultivariateDistribution" class "Distribution" by class "MultivariateDistribution".

Methods

show

signature(object = "MultivarMixingDistribution") prints the object

mixCoeff<-

signature(object = "MultivarMixingDistribution") replaces the corresponding slot

mixCoeff

signature(object = "MultivarMixingDistribution") returns the corresponding slot

mixDistr<-

signature(object = "MultivarMixingDistribution") replaces the corresponding slot

mixDistr

signature(object = "MultivarMixingDistribution") returns the corresponding slot

support

signature(object = "MultivarMixingDistribution") returns the corresponding slot

gaps

signature(object = "MultivarMixingDistribution") returns the corresponding slot

.logExact

signature(object = "Distribution"): returns slot .logExact if existing; else tries to convert the object to a newer version of its class by conv2NewVersion and returns the corresponding slot of the converted object.

.lowerExact

signature(object = "Distribution"): returns slot .lowerExact if existing; else tries to convert the object to a newer version of its class by conv2NewVersion and returns the corresponding slot of the converted object.

Symmetry

returns slot Symmetry if existing; else tries to convert the object to a newer version of its class by conv2NewVersion and returns the corresponding slot of the converted object.

plot

signature(x = "MultivarMixingDistribution", y = "missing"): plot for an spherically symmetric distribution; see plot-methods.

E

corresponding expectation — see E.

dimension

dim of the range space.

dim

synonym to dimension.

show

signature(object = "MultivarMixingDistribution"): show method for spherically symmetric distributions.

showobj

signature(object = "MultivarMixingDistribution"): showobj method for spherically symmetric distributions.

Author(s)

Peter Ruckdeschel peter.ruckdeschel@uni-oldenburg.de

See Also

Parameter-class, MultivariateDistribution-class, LatticeDistribution-class, AbscontDistribution-class, simplifyD-methods, flat.mix

Examples

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
mylist <- MultivarMixingDistribution(Binom(3,.3), Dirac(2), Norm(), 
          mixCoeff=c(1/4,1/5,11/20))
mylist2 <- MultivarMixingDistribution(Binom(3,.3), mylist, 
          mixCoeff=c(.3,.7))
mylist2
p(mylist)(0.3)          
mixDistr(mylist2)
E(mylist)
var(mylist)

##multivariate
E1 <- diag(1,2)%*%EllipticalDistribution(radDistr=Gammad())+c(1,2)
mylistD <- MultivarMixingDistribution(MVNorm(), E1, MVt(),
          mixCoeff=c(1/4,1/5,11/20))
mylistD2 <- MultivarMixingDistribution(E1+c(-2,2), mylistD,
          mixCoeff=c(.3,.7))
mylistD2
p(mylistD)
mixDistr(mylistD2)
E(mylistD2)
var(mylistD2)