# markovchain-package: Easy Handling Discrete Time Markov Chains In markovchain: 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: 0.6.9.10 Date: 2018-05-30 License: GPL-2 Depends: R (>= 3.4.0), methods, expm, matlab, igraph, Matrix

## Author(s)

Giorgio Alfredo Spedicato Maintainer: Giorgio Alfredo Spedicato <[email protected]>

## References

Discrete-Time Markov Models, Bremaud, Springer 1999

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27``` ```#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) ```

markovchain documentation built on Aug. 24, 2018, 1:03 a.m.