Lotka Predator-Prey model
In GillespieSSA2: Gillespie's Stochastic Simulation Algorithm for Impatient People

set.seed(1)
knitr::opts_chunk$set(fig.width = 6, fig.height = 4)
if("package:GillespieSSA" %in% search()) detach("package:GillespieSSA", unload=TRUE)

This version of the Lotka predator-prey model [@Gillespie1977; @Kot2001] is given by

dY1/dt = c1*Y1 - c2*Y1*Y2
dY2/dt = c2*Y1*Y2 - c3*Y2

consisting of the three reaction channels,

      Y1 --c1--> Y1 + Y1 
 Y1 + Y2 --c2--> Y2 + Y2 
      Y1 --c3--> 0

Define parameters

library(GillespieSSA2)
sim_name <- "Lotka Predator-Prey model"
params <- c(c1 = 10, c2 = .01, c3 = 10)
final_time <- 2
initial_state <- c(Y1 = 1000, Y2 = 1000)

Define reactions

reactions <- list(
  reaction("c1 * Y1", c(Y1 = +1)),
  reaction("c2 * Y1 * Y2", c(Y1 = -1, Y2 = +1)),
  reaction("c3 * Y2", c(Y2 = -1))
)

Run simulations with the Exact method

set.seed(1)
out <- ssa(
  initial_state = initial_state,
  reactions = reactions,
  params = params,
  final_time = final_time,
  method = ssa_exact(),
  sim_name = sim_name
) 
plot_ssa(out)

Run simulations with the Explict tau-leap method

set.seed(1)
out <- ssa(
  initial_state = initial_state,
  reactions = reactions,
  params = params,
  final_time = final_time,
  method = ssa_etl(tau = .002),
  sim_name = sim_name
) 
plot_ssa(out)

Run simulations with the Binomial tau-leap method

set.seed(1)
out <- ssa(
  initial_state = initial_state,
  reactions = reactions,
  params = params,
  final_time = final_time,
  method = ssa_btl(mean_firings = 100),
  sim_name = sim_name
) 
plot_ssa(out)