Use the results of a simulation to set the radiocarbon measurements (rc_meas) for an analysis (and store the settings used to do the simulation)

This is one of a set of helper functions for undertaking a typical analysis of radiocarbon dates. As the analysis proceeds, results are stored in a save file called analysis_name.rds in the folder data_dir. Where results are non-deterministic, random number seeds are set and stored to ensure that, even if processing is interrupted, results are fully reproducible.

There are, in fact, two distinct pipelines for (a) simulations and (b) analyses that use existing radiocarbon measurements saved in a .csv file. Since this is the first helper function used in the standard pipeline for simulations, that pipeline is described here. See set_rc_meas for the pipeline when using an input .csv file.

The standard pipeline for simulations is (see the vignette standard_pipeline for additional details):

(0) simulate_rc_data Define the simulation parameters and create simulated data using simulate_rc_data.

(1) set_sim Set the simulated data for the analysis

(2) calc_tau_range Determine the range of calendar dates that span the radiocarbon measurements (or specify the range directly)

(3) set_density_model Set the parametric model to be used for Bayesian inference. Currently, only a truncated Gaussian mixture is supported, which requires setting the calendar date range for truncation (likely using the result from step (3)) and choosing the number of mixture components, K. If K is a vector, Bayesian inference will be done for each element of the vector during step (4), do_bayesian_inference.

(4) do_bayesian_inference Call sample_theta to do the Bayesian inference for each model to check. (Unlike the other pipeline that starts with an input .csv file, set_calib_curve does not need to be called prior to this step since the calibration curve is set with set_sim.)

(5) do_bayesian_summary Calculate summary statistics for the best model sampled by calling do_bayesian_inference (the best model is the one with the best WAIC).

(6) plot_best_solution Create a plot of the best solution.

set_sim(data_dir, analysis_name, sim)

Arguments

data_dir	The directory in which to store analysis data
analysis_name	A unique name for a given analysis in data_dir
sim	The simulation object (see simulate_rc_data)