Simulate from an estimated Nonmem model

Supply a data set and an estimation input control stream, and NMsim can create neccesary files (control stream, data files), run the simulation and read the results. It has additional methods for other simulation types available, can do multiple simulations at once and more. Please see vignettes for an introduction to how to get the most out of this.

Usage

NMsim(
  file.mod,
  data,
  subproblems = NULL,
  reuse.results = FALSE,
  seed.R,
  seed.nm,
  name.sim,
  table.vars,
  table.options,
  table.format,
  carry.out = TRUE,
  method.sim = NMsim_default,
  typical = FALSE,
  inits,
  modify,
  filters,
  sizes,
  path.nonmem = NULL,
  sge = FALSE,
  nc = 1,
  execute = TRUE,
  script = NULL,
  transform = NULL,
  order.columns = TRUE,
  method.execute,
  nmrep,
  col.flagn = FALSE,
  sim.dir.from.scratch = TRUE,
  create.dirs = TRUE,
  dir.psn,
  args.psn.execute,
  args.NMscanData,
  as.fun,
  system.type = NULL,
  dir.sims,
  dir.res,
  file.res,
  wait,
  text.sim = "",
  auto.dv = TRUE,
  clean,
  quiet = FALSE,
  nmquiet,
  progress,
  check.mod = TRUE,
  format.data.complete = "rds",
  text.table,
  suffix.sim,
  seed,
  file.ext = NULL,
  method.update.inits,
  modify.model,
  list.sections,
  ...
)

Arguments

file.mod

Path(s) to the input control stream(s) to run the simulation on. The output control stream is for now assumed to be stored next to the input control stream and ending in .lst instead of .mod. The .ext file must also be present. If simulating known subjects, the .phi is necessary too.

data

The simulation data as a data.frame or a list of data.frames. If a list, the model(s) will be run on each of the data sets in the list.

subproblems

Number of subproblems to use as SUBPROBLEMS in $SIMULATION block in Nonmem. The default is subproblem=0 which means not to use SUBPROBLEMS.

reuse.results

If simulation results found on file, should they be used? If TRUE and reading the results fail, the simulations will still be rerun.

seed.R

A value passed to set.seed(). It is recommended to use seed.R rather than calling set.seed() manually because the seed can then be captured and stored by NMsim() for reproducibility. See seed.nm for finer control of the seeds that are used in the Nonmem control streams.

seed.nm

Control Nonmem seeds. If a numeric, a vector or a `data.frame`, these are used as the the seed values (a single value or vector will be recycled so make sure the dimesnsions are right, the number of columns in a data.frame will dictate the number of seeds in each Nonmem control stream. Use a list with elements `values`, and `dist` and others for detailed control of the random sources. See ?NMseed for details on what arguments can be passed this way.

Default is to draw seeds betwen 0 and 2147483647 (the values supported by Nonmem) for each simulation. You can pass a function that will be evaluated (say to choose a different pool of seeds to draw from).

To avoid changing an exisiting seed in a control stream, use seed.nm="asis".

In case method.sim=NMsim_EBE, seeds are not used.

name.sim

Give all filenames related to the simulation a suffix. A short string describing the sim is recommended like "ph3_regimens".

table.vars

Variables to be printed in output table as a character vector or a space-separated string of variable names. The default is to export the same tables as listed in the input control stream. If table.vars is provided, all output tables in estimation control streams are dropped and replaced by a new one with just the provided variables. If many variables are exported, and much fewer are used, it can speed up NMsim significantly to only export what is needed (sometimes this is as little as "PRED IPRED"). Nonmem writes data slowly so reducing output data can make a very big difference in execution time. See table.options too.

table.options

A character vector or a string of space-separated options. Only used if table.vars is provided. If constructing a new output table with table.vars the default is to add two options, NOAPPEND and NOPRINT. You can modify that with table.options. Do not try to modify output filename - NMsim takes care of that.

table.format

A format for `$TABLE`. Only used if `table.vars` is provided.

carry.out

Variables from input data that should be included in results. Default is to include everything. If working with large data sets, it may be wanted to provide a subset of the columns here. If doing very large simulations, this may also be a way to save memory.

method.sim

A function (not quoted) that creates the simulation control stream and other necessary files for a simulation based on the estimation control stream, the data, etc. The default is called NMsim_default which will replace any estimation and covariance step by a simulation step. See details section on oter methods, and see examples and especially vignettes on how to use the different provided methods.

typical

Run with all ETAs fixed to zero? Technically all ETAs=0 is obtained by replacing $OMEGA by a zero matrix. Default is `FALSE`.

inits

Control the parameter values. `inits` is a list. The `method` element controls which method is used to do this, and this corresponds to the old `method.update.inits` argument. If using the new `method=nmsim` you can specify parameter values, fix/unfix them, and edit lower and upper limits for estimation.

• `method="nmsim"`, all other arguments are passed to `NMwriteInits`. This is a flexible method that allows for modification of the parameter values and is expected to be the default method in the future. Example which will update the parameter values based on the available estimate, but with `THETA(2)=1.3`: `inits=list(method="nmsim","THETA(2)"=list(init=1.3))`. See `?NMwriteInits` too.

• `method="psn"` uses PSN's "update_inits". Requires a functioning PSN installation and possibly that dir.psn is correctly set. The advantages of this method are that it keeps comments in the control stream and that it is a method known to many.

• `method="nmsim"` Uses a simple internal method to update the parameter values based on the ext file. The advantages of "nmsim" are it does not require PSN, and that it does not rely on code-interpretation for generation of simulation control streams. "nmsim" fixes the whole OMEGA and SIGMA matrices as single blocks making the $OMEGA and $SIGMA sections of the control streams less easy to read. On the other hand, this method is robust because it avoids any interpretation of BLOCK structure or other code in the control streams.

• `method="none"` Do nothing. This is useful if the model to simulate has not been estimated but parameter values have been manually put into the respective sections in the control stream.

See also `file.ext` which can now be handled by `inits` too. This change collects the update of the "initial" parameter values into one interface rather than multiple arguments.

modify

Named list of additional control stream section edits. Note, these can be functions that define how to edit sections. This is an advanced feature which is not needed to run most simulations. It is however powerful for some types of analyses, like modifying parameter values. See vignettes for further information.

filters

Edit data filters (`IGNORE`/`ACCEPT` statements) before running model. This should normally only be used if no data set is provided. It can be useful if simulating for a VPC but a different subset of data needs to be simulated than the one used for estimation. A common example on this is inclusion of BLQ's in the VPC even if they were excluded in the estimation. See `?NMreadFilters` which returns a table you can edit and pass to `filters`. You can also just pass a string representing the full set of filters to be used. If you pass a string, consider including "IGN=@" to avoid character rows, like the column headers.

sizes

If needed, adjust the `$SIZES` section by providing a list of arguments to `NMupdateSizes()`. Example: `sizes=list(PD=80)`. See `?NMupdateSizes` for details. Don't use arguments like `file.mod` and `newfile` which are handled internally.

path.nonmem

The path to the Nonmem executable to use. The could be something like "/usr/local/NONMEM/run/nmfe75" (which is a made up example). No default is available. You should be able to figure this out through how you normally execute Nonmem, or ask a colleague.

sge

Submit to cluster? Default is not to, but this is very useful if creating a large number of simulations, e.g. simulate with all parameter estimates from a bootstrap result.

nc

Number of cores used in parallelization. Only used if `sge=TRUE`.

execute

Execute the simulation or only prepare it? `execute=FALSE` can be useful if you want to do additional tweaks or simulate using other parameter estimates.

script

The path to the script where this is run. For stamping of dataset so results can be traced back to code.

transform

A list defining transformations to be applied after the Nonmem simulations and before plotting. For each list element, its name refers to the name of the column to transform, the contents must be the function to apply.

order.columns

reorder columns by calling NMdata::NMorderColumns before saving dataset and running simulations? Default is TRUE.

method.execute

Specify how to call Nonmem. Options are "psn" (PSN's execute), "nmsim" (an internal method similar to PSN's execute), and "direct" (just run Nonmem directly and dump all the temporary files). "nmsim" has advantages over "psn" that makes it the only supported method when type.sim="NMsim_EBE". "psn" has the simple advantage that the path to nonmem does not have to be specified if "execute" is in the system search path. So as long as you know where your Nonmem executable is, "nmsim" is recommended. The default is "nmsim" if path.nonmem is specified, and "psn" if not.

nmrep

Include `NMREP` as counter of subproblems? The default is to do so if `subproblems>0`. This will insert a counter called `NMREP` in the `$ERROR` section and include that in the output table(s). At this point, nothing is done to avoid overwriting existing variables.

col.flagn

Only used if `data` is provided. Use this if you are including an exclusion flag column in data. However, what NMsim will then do is to require that column to equal `0` (zero) for the rows to be simulated. It is often better to subset the data before simulation. See `filters` too.

sim.dir.from.scratch

If TRUE (default) this will wipe the simulation directory before running new simulations. The directory that will be emptied is _not_ dir.sims where you may keep many or all your simulations. It is the subdirectory named based on the run name and name.sim. The reason it is advised to wipe this directory is that if you in a previous simulation created simulation runs that are now obsolete, you could end up reading those too when collecting the results. NMsim will delete previously generated simulation control streams with the same name, but this option goes further. An example where it is important is if you first ran 1000 replications, fixed something and now rand 500. If you choose FALSE here, you can end up with the results of 500 new and 500 old simulations.

create.dirs

If the directories specified in dir.sims and dir.res do not exists, should it be created? Default is TRUE.

dir.psn

The directory in which to find PSN's executables ('execute' and 'update_inits'). The default is to rely on the system's search path. So if you can run 'execute' and 'update_inits' by just typing that in a terminal, you don't need to specify this unless you want to explicitly use a specific installation of PSN on your system.

args.psn.execute

A charachter string that will be passed as arguments PSN's `execute`.

args.NMscanData

If table.options is used, NMsim turns to `NMdata::NMscanData()` for a general method to read the output tables. Use `args.NMscanData` to pass additional arguments (in a list) to that function if you want the results to be read in a specific way. This can be if the model for some reason drops rows, and you need to merge by a row identifier. You would do `args.NMscanData=list(col.row="ROW")` to merge by a column called `ROW`. This is only used in rare cases. Better just stick to NMsim's optimized default `table.options` and related methods for reading results.

as.fun

The default is to return data as a data.frame. Pass a function (say `tibble::as_tibble`) in as.fun to convert to something else. If data.tables are wanted, use as.fun="data.table". The default can be configured using NMdataConf.

system.type

A charachter string, either \"windows\" or \"linux\" - case insensitive. Windows is only experimentally supported. Default is to use Sys.info()[["sysname"]].

dir.sims

The directory in which NMsim will store all generated files. Default is to create a folder called `NMsim` next to `file.mod`.

dir.res

Provide a path to a directory in which to save rds files with paths to results. Default is to use dir.sims. After running `NMreadSim()` on these files, the original simulation files can be deleted. Hence, providing both `dir.sims` and `dir.res` provides a structure that is simple to clean. `dir.sims` can be purged when `NMreadSim` has been run and only small `rds` and `fst` files will be kept in `dir.res`. Notice, in case multiple models are simulated, multiple `rds` (to be read with `NMreadSim()`) files will be created by default. In cases where multiple models are simulated, see `file.res` to get just one file refering to all simulation results.

file.res

Path to an rds file that will contain a table of the simulated models and other metadata. This is needed for subsequently retrieving all the results using `NMreadSim()`. The default is to create a file called `NMsim_..._MetaData.rds` under the dir.res directory where ... is based on the model name. However, if multiple models (file.mod) are simulated, this will result in multiple rds files. Specifying a path ensures that one rds file containing information about all simulated models will be created. Notice if file.res is supplied, dir.res is not used.

wait

Wait for simulations to finish? Default is to do so if simulations are run locally but not to if they are sent to the cluster. Waiting for them means that the results will be read when simulations are done. If not waiting, path(s) to `rds` files to read will be returned. Pass them through `NMreadSim()` (which also supports waiting for the simulations to finish).

text.sim

A character string to be pasted into $SIMULATION. This must not contain seed or SUBPROBLEM which are handled separately. Default is to include "ONLYSIM". You cannot avoid that using `text.sim`. Instead, you can use `onlysim=FALSE` which will be passed to `NMsim_default()`.

auto.dv

Add a column called `DV` to input data sets if a column of that name is not found? Nonmem is generally dependent on a `DV` column in input data but this is typically uninformative in simulation data sets and hence easily forgotten when generating simulation data sets. If auto.dv=TRUE and no `DV` column is found, `DV=NA` will be added. In this case (`auto.dv=TRUE` and no `DV` column found) a `MDV=1` column will also be added if none found.

clean

The degree of cleaning (file removal) to do after Nonmem execution. If `method.execute=="psn"`, this is passed to PSN's `execute`. If `method.execute=="nmsim"` a similar behavior is applied, even though not as granular. NMsim's internal method only distinguishes between 0 (no cleaning), any integer 1-4 (default, quite a bit of cleaning) and 5 (remove temporary dir completely).

quiet

If TRUE, messages from what is going on will be suppressed.

nmquiet

Silent console messages from Nonmem? The default behaviour depends. It is FALSE if there is only one model to execute and `progress=FALSE`.

progress

Track progress? Default is `TRUE` if `quiet` is FALSE and more than one model is being simulated. The progress tracking is based on the number of models completed, not the status of the individual models.

check.mod

Check the provided control streams for contents that may cause issues for simulation. Default is `TRUE`, and it is only recommended to disable this if you are fully aware of such a feature of your control stream, you know how it impacts simulation, and you want to get rid of warnings.

format.data.complete

For development purposes - users do not need this argument. Controls what format the complete input data set is saved in. Possible values are `rds` (default), `fst` (experimental) and `csv`. `fst` may be faster and use less disk space but factor levels may be lost from input data to output data. `csv` will also lead to loss of additional information such as factor levels.

text.table

Deprecated. Use `table.vars` and `table.options` instead.

suffix.sim

Deprecated. Use name.sim instead.

seed

Deprecated. See seed.R and seed.nm.

file.ext

Depecated. Use `inits=list(file.ext="path/to/file.ext")` instead. Optionally provide a parameter estimate file from Nonmem. This is normally not needed since `NMsim` will by default use the ext file stored next to the input control stream (replacing the file name extension with `.ext`). If using method.update.inits="psn", this argument cannot be used.

method.update.inits

Deprecated, please migrate to `inits` instead. The initial values of all parameters are by updated from the estimated model before running the simulation. NMsim can do this with a native function or use PSN to do it - or the step can be skipped to not update the values.

modify.model

Deprecated. Use modify instead.

list.sections

Deprecated. Use modify instead.

...

Additional arguments passed to method.sim.

Value

A data.frame with simulation results (same number of rows as input data). If `sge=TRUE` a character vector with paths to simulation control streams.

Details

Loosely speaking, the argument method.sim defines _what_ NMsim will do, method.execute define _how_ it does it. method.sim takes a function that converts an estimation control stream into whatever should be run. Features like replacing `$INPUT`, `$DATA`, `$TABLE`, and handling seeds are NMsim features that are done in addition to the method.sim. Also the modeify.model argument is handled in addition to the method.sim. The subproblems and seed.nm arguments are available to all methods creating a $SIMULATION section.

Notice, the following functions are internally available to `NMsim` so you can run them by say method.sim=NMsim_EBE without quotes. To see the code of that method, type NMsim_EBE.

• NMsim_default The default behaviour. Replaces any $ESTIMATION and $COVARIANCE sections by a $SIMULATION section.

• NMsim_asis The simplest of all method. It does nothing (but again, NMsim handles `$INPUT`, `$DATA`, `$TABLE` and more. Use this for instance if you already created a simulation (or estimation actually) control stream and want NMsim to run it on different data sets.

• NMsim_EBE Simulates _known_ ETAs. By default, the ETA values are automatically taken from the estimation run. This is what is refered to as emperical Bayes estimates, hence the name of the method "NMsim_EBE". However, the user can also provide a different `.phi` file which may contain simulated ETA values (see the `file.phi` argument). ID values in the simulation data set must match ID values in the phi file for this step to work. If refering to estimated subjects, the .phi file from the estimation run must be found next to the .lst file from the estimation with the same file name stem (say `run1.lst` and `run1.phi`). Again, ID values in the (simulation) input data must be ID values that were used in the estimation too. The method Runs an $ESTIMATION MAXEVAL=0 but pulls in ETAs for the ID's found in data. No $SIMULATION step is run which unfortunately means no residual error will be simulated.

• NMsim_VarCov Like NMsim_default but `$THETA`, `$OMEGA`, and `SIGMA` are drawn from distribution estimated in covariance step. This means that a successful covariance step must be available from the estimation. NB. A multivariate normal distribution is used for all parameters, including `$OMEGA` and `$SIGMA` which is not the correct way to do this. In case the simulation leads to negative diagonal elements in $OMEGA and $SIGMA, those values are truncated at zero. This method is only valid for simulation of `$THETA` variability. The method accepts a table of parameter values that can be produced with other tools than `NMsim`. For simulation with parameter variability based on bootstrap results, use NMsim_default.

• NMsim_typical Deprecated. Use typical=TRUE instead.