R: Easy Handling Discrete Time Markov Chains

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

### Details

Package: | markovchain
Type: | Package
Version: | 0.8.2
Date: | 2020-01-5
License: | GPL-2
Depends: | R (>= 3.6.0), methods, expm, matlab, igraph, Matrix

### 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 0.8.6 Index]