ValidationExplorer (version 0.1.1)

plot_coverage_vs_calls: plot_coverage_vs_calls: Compare validation designs based on coverage of 95% posterior intervals and expected level of effort

Description

plot_coverage_vs_calls: Compare validation designs based on coverage of 95% posterior intervals and expected level of effort

Usage

plot_coverage_vs_calls(
  sim_summary,
  calls_summary,
  pars = NULL,
  regex_pars = NULL,
  theta_scenario,
  scenarios,
  max_calls = NULL,
  convergence_threshold = 1.1
)

Value

A ggplot2 object showing the number of calls validated on the x-axis and the average coverage of 95% credible intervals on the y-axis.

Arguments

sim_summary

Simulation summary from many datasets under many validation scenarios in the format output by mcmc_sum.

calls_summary

Summary of the validation design in the format as output from summarize_n_validated

pars

A character vector of parameters to visualize.

regex_pars

String containing the name of a group of parameters to visualize. Must be one of "lambda", "psi", or "theta".

theta_scenario

String containing the theta scenario ID that was used to run simulations in run_sims. This string must match between calls_summary and sim_summary.

scenarios

A vector of integers corresponding to the validation designs you would like to visualize.

max_calls

The maximum number of calls that can be manually reviewed. All points beyond this threshold will be shaded gray in the plot. Default value is NULL.

convergence_threshold

A threshold for the Gelman-Rubin statistic; values below this threshold (and near 1) indicate that a parameter has converged.

Examples

sim_summary <- example_output
calls_summary <- example_val_sum

plot_coverage_vs_calls(sim_summary, calls_summary, regex_pars = "lambda",
                   theta_scenario = "1", scenarios = 1:2,
                   convergence_threshold = 1.05)