mc-package: Markov Chain Model

In yuki0425/mc: Markov Chain Model

Description

This package contains several functions to handle and analysis both discrete and continous time Markov Chain Model with infinite and finite states.

Author(s)

Jiexuan Cao,Yuki Liu, Qianhan Zhang

Maintainer: Jiexuan Cao <[e-mail]>

References

Matloff, Norm. "Chapter 6: Introduction to Discrete Markov Chains." From Algorithms to Z-Scores: Probabilistic and Statistical Modeling in Computer Science. Davis: U of California, 2014. 109-23. Print.

Examples

## discrete finite Markov Chain
dtftmc = mc(states = c("sunny", "cloudy", "rain"),
                 pijdef = function(i,j,...) {
                           if (i == 1 && j < 3 ||
                               i == 2 && j != 2 ||
                               i == 3 && j > 1)  return(0.5)
                           0
                        },
       name = "Weather")


## discrete infinite Markov Chain
pijdeffunction = function(i,j) {
    p = 0.3
    q = 0.7
    r = 0
    if (i == 1 && j == 1)
        return (1 - p)
    if(j == i + 1)
        return(p)
    if(j == i - 1)
        return(q)
    if(j==i)
        return(r)
    return(0)
}

dtiftmc = mc(states = "infinity",
             pijdef = pijdeffunction,
             name = "death and birth")

## get states of the Markov Chain
dtftmc$states
dtiftmc$states

## get transition matrix of the Markov Chain
dtftmc$pijdef
dtiftmc$pijdef

##get stationary distribution of the Markov Chain function
dtftsd = stn(dtftmc)
dtiftsd = stn(dtiftmc)

##get submatrix of expected hitting times function, with rows and columns specified by the user as i j.
dtftht = hittingtime(dtftmc, c(1,2), c(2,3))
dtiftht = hittingtime(dtiftmc, c(1,2), c(2,3))

yuki0425/mc documentation built on May 4, 2019, 7:44 p.m.