Non-homogeneous discrete time Markov chain class
Source:R/classesAndMethods.R
markovchainList-class.RdThe S4 class of non-homogeneous discrete time Markov chains:
a sequence of markovchain objects, the \(k\)-th
giving the transition probabilities from time \(k - 1\) to time
\(k\).
Slots
markovchainsA list of
markovchainobjects.nameOptional name of the object.
Note
The class consists in a list of markovchain objects.
It is aimed at working with non homogeneous Markov chains.
Objects from the Class
Objects are created with new("markovchainList", markovchains = list(...))
or estimated by markovchainListFit(). The transition probabilities, and
the states, may change from one time to the next.
Methods
- [[
signature(x = "markovchainList"): extract the i-thmarkovchain- dim
signature(x = "markovchainList"): number ofmarkovchainunderlying the matrix- predict
signature(object = "markovchainList"): predict from amarkovchainListsignature(x = "markovchainList"): prints the list of markovchains- show
signature(object = "markovchainList"): same asprint
Examples
showClass("markovchainList")
#> Class "markovchainList" [package "markovchain"]
#>
#> Slots:
#>
#> Name: markovchains name
#> Class: list character
#define a markovchainList
statesNames=c("a","b")
mcA<-new("markovchain",name="MCA",
transitionMatrix=matrix(c(0.7,0.3,0.1,0.9),
byrow=TRUE, nrow=2,
dimnames=list(statesNames,statesNames))
)
mcB<-new("markovchain", states=c("a","b","c"), name="MCB",
transitionMatrix=matrix(c(0.2,0.5,0.3,0,1,0,0.1,0.8,0.1),
nrow=3, byrow=TRUE))
mcC<-new("markovchain", states=c("a","b","c","d"), name="MCC",
transitionMatrix=matrix(c(0.25,0.75,0,0,0.4,0.6,
0,0,0,0,0.1,0.9,0,0,0.7,0.3),
nrow=4, byrow=TRUE)
)
mcList<-new("markovchainList",markovchains=list(mcA, mcB, mcC),
name="Non - homogeneous Markov Chain")