A first example | Introduction | Workflow | Defining the data.frames for data generation and analysis | The workhorse eval_tibbles | Parameter replications | Parameter discard_generated_data | Parameter summary_fun | Parameter post_analyze | Parameter group_for_summary | Parameter ncpus and cluster_seed | Parameter cluster | Parameter cluster_libraries and cluster_global_objects | Parameter envir | .truth-functionality | Some Examples | Sampling distribution of mean and median for normal and exponential distributed data | Comparing bootstrap confidence intervals with classical studentized interval | Define and run the simulation | A different implementation

Core functionality | Convenience functions