run_mcstudy: Run the Monte Carlo study by KLTG (2020), or a smaller version thereof

Description

Run the Monte Carlo study by KLTG (2020), or a smaller version thereof

Usage

run_mcstudy(
  s = 2,
  a = 0.5,
  n = 12,
  nr_iterations = 50,
  zoom = FALSE,
  random_seed = 816
)

Value

Object of class "mcstudy", containing the results of the analysis. This object can be passed to plot for plotting, see the documentation for plot.mcstudy.

Arguments

s, a, n: parameters characterizing the process from which data are simulated (see Section 4 and Table 4 of KLTG, 2019). Defaults to the values reported in the main text of the paper.
nr_iterations: number of Monte Carlo iterations (defaults to 50).
zoom: set to TRUE to produce results for a fine grid of small (MCMC) sample sizes, as in Figure 2 of KLTG (2020).
random_seed: seed used for running the simulation experiment. Defaults to 816.

Author

Fabian Krueger

Details

The full results in Section 4 of KLTG (2020) are based on s = 2, a = 0.5, n = 12 and nr_iterations = 1000. Producing these results takes about 140 minutes on an Intel i7 processor.

References

Krueger, F., Lerch, S., Thorarinsdottir, T.L. and T. Gneiting (2020): `Predictive inference based on Markov chain Monte Carlo output', International Statistical Review, forthcoming. tools:::Rd_expr_doi("10.1111/insr.12405")