This function can be used to estimate the expected amount of time needed for a specific number of transitions to be realized (in which case event.target should be supplied) or the expected number of transition events occurring within a specified time period (in which case time.target should be supplied). Either way, one of time.target and event.target must be given. The function works by simulating reps trajectories (using simEGP) for the specified time/number of events, and returning the mean outcome (along with some other associated statistics).
A typical use case for this function is to calibrate the simulation time needed to obtain a reasonable number of transitions from some starting point (e.g., to ensure burn-in). Simply simulating a fixed number of transition events will result in a biased system state; however, one can avoid this problem by using this function to determine the average duration needed for the desired number of events to be realized, and then using this duration as a stopping rule for subsequent simulations. Alternately, another use is to estimate the rate at which events accrue, e.g. to estimate compute time or memory requirements for a longer simulation study. Some processes are particularly prone to entering regimes in which they produce very large numbers of events per unit phenomenological time, and it can be useful to identify this issue before committing resources to simulating a long trajectory.
Note that, at present, all trajectories have the same starting point (the network on the left-hand side of the input formula). They are hence coupled by the initial condition (despite being otherwise independent). When equilibrium estimates from short sequences are desired, it may be wise to call this function more than once with different starting networks and integrate the results.