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

1 |

`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" |

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

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.

Sai Bhargav Yalamanchi

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

`generatorToTransitionMatrix`

,`ctmc-class`

1 2 3 4 5 6 7 8 9 10 11 12 | ```
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)
``` |

Questions? Problems? Suggestions? Tweet to @rdrrHQ or email at ian@mutexlabs.com.

All documentation is copyright its authors; we didn't write any of that.