R: rctmc

rctmc {markovchain} | R Documentation

## rctmc

### Description

The function generates random CTMC transitions as per the provided generator matrix.

### Usage

    rctmc(n, ctmc, initDist = numeric(), T = 0, include.T0 = TRUE,
      out.type = "list")

### Arguments

`n` | The number of samples to generate.
`ctmc` | The CTMC S4 object.
`initDist` | The initial distribution of states.
`T` | The time up to which the simulation runs (all transitions after time T are not returned).
`include.T0` | Flag to determine if start state is to be included.
`out.type` | "list" or "df"

### Details

In order to use the T0 argument, set n to Inf.

### Value

Based on out.type, a list or a data frame is returned. The returned list has two elements - a character vector (states) and a numeric vector (indicating time of transitions). The data frame is similarly structured.

### Author(s)

Sai Bhargav Yalamanchi

### References

Introduction to Stochastic Processes with Applications in the Biosciences (2013), David F. Anderson, University of Wisconsin at Madison

### See Also

`generatorToTransitionMatrix`,`ctmc-class`

### Examples

    energyStates <- c("sigma", "sigma_star")
    byRow <- TRUE
    gen <- matrix(data = c(-3, 3, 1, -1), nrow = 2,
                 byrow = byRow, dimnames = list(energyStates, energyStates))
    molecularCTMC <- new("ctmc", states = energyStates,
                         byrow = byRow, generator = gen,
                         name = "Molecular Transition Model")

    statesDist <- c(0.8, 0.2)
    rctmc(n = Inf, ctmc = molecularCTMC, T = 1)
    rctmc(n = 5, ctmc = molecularCTMC, initDist = statesDist, include.T0 = FALSE)

[Package markovchain version 0.8.6 Index]