markovchain-package {markovchain} | R Documentation |
Easy Handling Discrete Time Markov Chains
Description
The package contains classes and method to create and manage (plot, print, export for example) discrete time Markov chains (DTMC). In addition it provide functions to perform statistical (fitting and drawing random variates) and probabilistic (analysis of DTMC proprieties) analysis
Author(s)
Giorgio Alfredo Spedicato Maintainer: Giorgio Alfredo Spedicato <spedicato_giorgio@yahoo.it>
References
Discrete-Time Markov Models, Bremaud, Springer 1999
Examples
# create some markov chains
statesNames=c("a","b")
mcA<-new("markovchain", transitionMatrix=matrix(c(0.7,0.3,0.1,0.9),byrow=TRUE,
nrow=2, dimnames=list(statesNames,statesNames)))
statesNames=c("a","b","c")
mcB<-new("markovchain", states=statesNames, transitionMatrix=
matrix(c(0.2,0.5,0.3,0,1,0,0.1,0.8,0.1), nrow=3,
byrow=TRUE, dimnames=list(statesNames, statesNames)))
statesNames=c("a","b","c","d")
matrice<-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)
mcC<-new("markovchain", states=statesNames, transitionMatrix=matrice)
mcD<-new("markovchain", transitionMatrix=matrix(c(0,1,0,1), nrow=2,byrow=TRUE))
#operations with S4 methods
mcA^2
steadyStates(mcB)
absorbingStates(mcB)
markovchainSequence(n=20, markovchain=mcC, include=TRUE)
[Package markovchain version 0.9.5 Index]