Mobius.capacity-class {kappalab} | R Documentation |
Class "Mobius.capacity"
Description
Class representing the Möbius transform of a capacity.
Objects from the Class
Objects can be mainly created by calls
to the functions Mobius.capacity
,
mini.var.capa.ident
,
ls.sorting.capa.ident
,
and least.squares.capa.ident
.
Slots
n
:Object of class
numeric
of length 1 containing the number of elements of the set on which the Möbius transform is defined.k
:Object of class
numeric
of length 1 containg the order of truncation of the Möbius transform: the value of subsets whose cardinal is superior to k is put to zero.subsets
:Object of class
numeric
containing the "k
power set" of the underlying set in "natural" order . The subsets are encoded as integers.data
:Object of class
numeric
of lengthchoose(n,0) + ... + choose(n,k)
representing the coefficients of a truncated Möbius transform of a capacity in "natural" order.
Extends
Class Mobius.game
, directly.
Class superclass.capacity
, directly.
Class Mobius.set.func
, by class Mobius.game
.
Class superclass.set.func
, by class Mobius.game
.
Methods
- entropy
signature(object = "Mobius.capacity")
- favor
signature(object = "Mobius.capacity")
- is.normalized
signature(object = "Mobius.capacity")
- normalize
signature(object = "Mobius.capacity")
- orness
signature(object = "Mobius.capacity")
- variance
signature(object = "Mobius.capacity")
- veto
signature(object = "Mobius.capacity")
- zeta
signature(object = "Mobius.capacity")
See Also
capacity-class
,
entropy-methods
,
favor-methods
,
is.normalized-methods
,
orness-methods
,
variance-methods
,
veto-methods
,
zeta-methods
,
mini.var.capa.ident
,
least.squares.capa.ident
,
ls.sorting.capa.ident
.
Examples
## a capacity
mu <- capacity(c(0,0,0:13))
## and its Mobius representation
a <- Mobius(mu)
a
# the attributes of object a
a@n
a@k
a@data
a@subsets
## a test
is.normalized(a)
## normalize it
normalize(a)
## a transformation
zeta(a)
## Let us check ...
Mobius(zeta(a))
## some summary indices
orness(a)
veto(a)
favor(a)
variance(a)
entropy(a)
## the same
summary(a)