Skip to contents

These functions are called by mrgsim() and have explicit input requirements written into the function name. The motivation behind these variants is to give the user a clear workflow with specific, required inputs as indicated by the function name. Use mrgsim_q() instead to benchmark mrgsolve or to do repeated quick simulation for tasks like parameter optimization, sensitivity analyses, or optimal design.


mrgsim_e(x, events, idata = NULL, data = NULL, ...)

mrgsim_d(x, data, idata = NULL, events = NULL, ...)

mrgsim_ei(x, events, idata, data = NULL, ...)

mrgsim_di(x, data, idata, events = NULL, ...)

mrgsim_i(x, idata, data = NULL, events = NULL, ...)

mrgsim_0(x, idata = NULL, data = NULL, events = NULL, ...)



the model object


an event object


a matrix or data frame of model parameters, one parameter per row (see idata_set())


NMTRAN-like data set (see data_set())


passed to update() and do_mrgsim()


Important: all of these functions require that data, idata, and/or events be pass directly to the functions. They will not recognize these inputs from a pipeline.

  • mrgsim_e simulate using an event object

  • mrgsim_ei simulate using an event object and idata_set

  • mrgsim_d simulate using a data_set

  • mrgsim_di simulate using a data_set and idata_set

  • mrgsim_i simulate using a idata_set

  • mrgsim_0 simulate using just the model

  • mrgsim_q simulate from a data set with quicker turnaround (see mrgsim_q())