markovchainList-class: Non homogeneus discrete time Markov Chains class

Description

A class to handle non homogeneous discrete Markov chains

Arguments

markovchains

Object of class "list": a list of markovchains

name

Object of class "character": optional name of the class

Objects from the Class

A markovchainlist is a list of markovchain objects. They can be used to model non homogeneous discrete time Markov Chains, when transition probabilities (and possible states) change by time.

Methods

[[: signature(x = "markovchainList"): extract the i-th markovchain
dim: signature(x = "markovchainList"): number of markovchain underlying the matrix
predict: signature(object = "markovchainList"): predict from a markovchainList
print: signature(x = "markovchainList"): prints the list of markovchains
show: signature(object = "markovchainList"): same as print

References

A First Course in Probability (8th Edition), Sheldon Ross, Prentice Hall 2010

Examples

Run this code

# NOT RUN {
showClass("markovchainList")
#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")

# }