R: mrgsim variant functions

mrgsim_variants {mrgsolve} | R Documentation

## mrgsim variant functions

### Description

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.

### Usage

    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, ...)

### Arguments

`x` | the model object
`events` | an event object
`idata` | a matrix or data frame of model parameters, one parameter per row (see `idata_set()`)
`data` | NMTRAN-like data set (see `data_set()`)
`...` | passed to `update()` and `do_mrgsim()`

### Details

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()`)

### See Also

`mrgsim()`, `mrgsim_q()`, `qsim()`

[Package mrgsolve version 1.0.0 Index]