| mcsim {baorista} | R Documentation |
Monte-Carlo simulation on aoristic data
Description
Samples multiple sets of random dates from aoristic weights
Usage
mcsim(x, nsim = 1000)
Arguments
x |
A ProbMat class object |
nsim |
Number of Monte-Carlo simulations |
Details
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).
Value
An object of class mcsimres containing relevant metadata and a matrix with the number of events per time-block per Monte-Carlo simulation.
References
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