Samples multiple sets of random dates from aoristic weights
mcsim(x, nsim = 1000)An object of class mcsimres containing relevant metadata and a matrix with the number of events per time-block per Monte-Carlo simulation.
A ProbMat class object
Number of Monte-Carlo simulations
The function randomly assigns to each event a time-block based on its probability values (i.e. aoristic weight) and computes, for each time-block, the total number of simulated events. This process is repeated nsim time, allowing to estimate percentile-based intervals on the number of events per time-block (Crema 2012). It should be noted that while this approach accounts for chronological uncertainty, it provides only a description of the sample rather than the underlying population, and can be biased how the underlying archaeological periodisations define the time-spans of each event (see also Crema 2024 for discussion on limitations).
Crema, E. R. (2012). Modelling Temporal Uncertainty in Archaeological Analysis. Journal of Archaeological Method and Theory, 19(3), 440–461. doi:10.1007/s10816-011-9122-3 Crema, E.R. (2024). A Bayesian alternative to Aoristic analyses in archaeology. Archaeometry. doi:10.1111/arcm.12984