The function generates random CTMC transitions as per the provided generator matrix.
rctmc(n, ctmc, initDist = numeric(), T = 0, include.T0 = TRUE, out.type = "list")
| 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" |
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.
In order to use the T0 argument, set n to Inf.
Introduction to Stochastic Processes with Applications in the Biosciences (2013), David F. Anderson, University of Wisconsin at Madison
Sai Bhargav Yalamanchi
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)#> [[1]] #> [1] "sigma_star" #> #> [[2]] #> [1] 0 #>rctmc(n = 5, ctmc = molecularCTMC, initDist = statesDist, include.T0 = FALSE)#> [[1]] #> [1] "sigma_star" "sigma" "sigma_star" "sigma" "sigma_star" #> #> [[2]] #> [1] 0.6895934 0.8593646 0.9276973 1.4460141 1.6212271 #>