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Changelog

Source: NEWS.md

NMsim 0.1.6

Bugfixes

  • overwrite() is a helper function intended to use in NMsim()’s modify.model argument. It would not work correctly for strings containing some special, at least. Fixed.

NMsim 0.1.5

CRAN release: 2024-11-14

New features

  • NMreadSim() has a new argument called rm.tmp which is used to remove the intermediate NONMEM files if they are successfully read. Remember, NMreadSim() creates a compressed results data set which will be read by NMreadSim() in future function calls, so unless debugging is needed on the simulation control streams and files returned by NONMEM running the simulations, it may be better to delete the intermediate files altogether and save the disk space.

  • expandCovs() has a new argument reduce.ref which defaults to TRUE meaning that by default there will be only one reference combination. If FALSE expandCovs() will return one reference for each covariate. The forest plot can be evaluated with just one reference simulation.

  • New function summarizeCovs() introduced to summarize simulation results for forest plots. This function is closely related to expandCovs()

  • NMsim() no longer requires NONMEM to be available if reuse.results=TRUE and NONMEM does not need to be run.

Bugfixes

  • NMsim 0.1.4 would not submit jobs to cluster when number of cores was nc=1. Fixed. Workaround in 0.1.4, use nc=2.

  • NMsim 0.1.4 erroneously concluded jobs had failed when sent to the cluster if there was no existing queue. This is due to the exit status of qsub in such cases. This has been fixed. As a workaround in 0.1.4, just run your sim again once the queue has been initiated by the first NMsim called.

  • When NONMEM failed in 0.1.4, NMsim might not return debugging info. Fixed.

NMsim 0.1.4

CRAN release: 2024-11-02

New features

  • sampleParsSimpar() is a new function that automates sampling of parameter values from an estimated variance-variance matrix in a successful $COVARIANCE step using the simpar R package from Metrum Research Group. simpar is currently not on CRAN, so the user must install it from MPN or github to make use of sampleParsSimpar(). The sampled parameter values can be fed directly to NMsim using the NMsim_VarCov method making it very easy to simulate with parameter uncertainty based on simpar. I want to thank Sanaya Shroff for her outstanding work on this functionality and for her exciting work summarizing the available methods for simulation with parameter uncertainty which she will be sharing at ACoP 2024. Also a big thanks to Eric Anderson for helping out with adjusting the github workflows to pull simpar from MPN.

  • expandCovs() is a new function that puts together data sets for univariately varying covariates while keeping other at reference values. The function can derive both reference values and covariate values to simulate at by using i.e. median() and quantile().

  • NMsim()

    • Results are now equipped with three columns distinguishing simulated models. This separation of information makes it easier to summarize simulation results within/across models and/or within/across simulation of models.
      • model: The run name derived from file.mod.
      • name.sim: The same as provided in the name.sim argument.
      • model.sim The name of the generated model. In the simple case, this is model and name.sim combined. But in many cases, multiple models are being generated for each simulated control stream.
    • No longer requires a .ext file if updating parameter values using PSN’s update_inits. It is still recommended to keep the .ext file since it provides higher accuracy than the .lst file.

  • NMexec()

    • When submitting all updated models, NMexec() will now by default try to detect if a model is already running before submitting it.

    • Provides a summary of models to be submitted before starting to do so.

  • NMcreateDoses()

    • ADDL and II are now also separate arguments providing a simpler interface than the addl argument. The addl argument provides the advantage of being able to specify the two columns together in one data.frame, possibly including covariates.

    • add.lastonly is a new argument. If TRUE (default) and ADDL and II are of length 1, they are only applied to the last event in a dosing regimen.

    • col.id argument to specify name of subject id column or to omit altogether using col.id=NA.

    • Now checking that TIME is covering the length of all other arguments. In contrast to other arguments, it does not make much sense to try to extrapolate the TIME argument.

  • addEVID2() now has two arguments, TIME and TAPD which allow for specification of time since first dose and time after each dose at which to insert simulation records. The two can even be combined. TIME replaces the now deprecated time.sim argument, and TAPD is new.

Bugfixes

  • A bug most likely affecting most Windows users for execution of Nonmem has been fixed. If on Windows, you should upgrade to NMsim 0.1.4. Thank you to Boris Grinshpun for reporting this!

  • When using method.execute="nmsim" there was an issue with parallellization. This was not a major problem in most simulation applications, but it should now be fixed.

  • NMsim()

    • When not providing a simulation data set - typically a simulation for a VPC - NMsim() would fail with messages like
Error in `:=`((col.sim), ..name.sim) :
  Check that is.data.table(DT) == TRUE. Otherwise, := and `:=`(...) are defined for use in j, once only and in particular ways. See help(":=").

The issue has been fixed. If using NMsim 0.1.3 or earlier, the workaround is to do NMdataConf(as.fun="data.table"). Then after having the simulation results as a data.table, convert it with as.data.frame() or as preferred.

Notice, NMdataConf() affects the succeeding NMsim() calls but also other NMdata and NMsim function calls. When the VPC simulation has run, you may not want to continue recieving data.tables, you should reset the default value for as.fun: NMdataConf(as.fun=NULL) which will turn it back to returning data.frames by default. If you prefer tibbles, you can do NMdataConf(as.fun=tibble::as_tibble). Generally, if you prefer to work with something that is not data.frames (data.table and tibble the most common alternatives), it is recommended to use NMdataConf() to customize your default.

  • NMexec()
    • NMexec would fail running control streams named starting in numerals (like 1.mod) when sge=TRUE. This is due to the way sge job names are generated by NMexec(). Fixed by prepending “NMsim_” in these cases.
  • NMcreateDoses
    • Would in some cases create too many replicates if there were covariates on multiple arguments. Fixed.

NMsim 0.1.3

CRAN release: 2024-08-26

New features

  • NMsim()

    • New simulation method NMsim_NWPRI() to simulate with parameter uncertainty. This automates simulation with parameter uncertainty using Nonmem’s NWPRI subroutine for models with a successful covariance step. For now this method only works for THETA since we have found that the parameter distributions sampled for OMEGA and SIGMA do not always match the model estimates and therefore cannot be trusted. To ensure that only THETA are sampled and simulated, this method should only be run using the typical=TRUE argument. This method is much faster than the existing methods in NMsim for simulation with parameter uncertainty (NMsim_VarCov()). This method depends on NMdata version 0.1.7 or greater. Big thanks to Brian Reilly for his excellent work on this important contribution.

    • The add() function to be used in NMsim()’s modify.model argument now supports prepending and appending of text lines to control stream sections. The default is still to append and add("text",.pos="top") will now prepend “text”.

  • NMexec()

    • A “cleaning” feature has been added to NMexec(), removing some of the temporary files generated by Nonmem after ended execution. The interface is inspired by PSN’s clean argument supporting values 0 (no cleaning), 1-4 (quite some cleaning - so far no difference betwen these values), and 5 for complete deletion of the temporary directory. When using method.execute="PSN" NMsim calls PSN’s execute passing on the clean value.

    • Default number of cores to be used by NMexec() can be controlled using NMdataConf(nc=N) where N is the desired default. Notice, NMsim() will not use this default. This is because parallellization is not as commonly used in simulation as in estimation.

    • A useful backup feature has been added. Before execution, any existing results files related to a model are by default moved to a backup folder. The backup files are not

  • NMsimTestConf() - Function to summarize and test configuration. This is used internally and provides important debugging information.

  • readParsWide() - A function to read wide-format parameter tables - is now exported. This is useful when simulating with parameter values that have been sampled outside Nonmem, e.g. using the simpar package.

Bugfixes

  • NMexec() would fail on linux when run on models with multiple $TABLE statements. Fixed.

  • NMsim’s internal method to update parameter initial values had an issue running on models with $OMEGA block structures. Fixed.

  • NMreadSim() would fail if working directory had been changed. Fixed.

Other changes

  • addEVID2 will no longer add a DV=NA column if DV is not in the input data set.

NMsim 0.1.2

CRAN release: 2024-07-15

No changes since 0.1.1 except for disabling a test that was failing on some systems due to technical reasons.

NMsim 0.1.1

CRAN release: 2024-07-03

While no critical and generally only few bugs have been found in NMsim 0.1.0, NMsim 0.2.0 includes several improvements and upgrades. The interface feels smoother too. I want to thank Ron Keizer for feedback and advice.

New features

  • NMsim() has a much reduced and improved messaging to the user. If more than one model or data set is supplied or generated, progress trackers will be shown while starting Nonmem, while waiting for Nonmem to finish, and while collecting the simulation results.

  • The messages include information about where intermediate files and final results files are stored.

  • NMexec() has improved support for estimation. method.execute="nmsim" and method.execute="psn" both work on linux and windows, even though less thoroughly tested on windows. Thank you to Boris Grinshpun for testing.

  • Names of files containing final results from NMsim() have been renamed to be more intuitive. The previous _paths.rds will now be called _MetaData.rds. The results, once read and compressed, will be in a file called _ResultsData.fst. Notice, both these files are required to fully recover simulation results. Thanks to Brian Reilly for discussions on this and many other design aspects.

  • It is now possible to provide specific parameters (THETA, OMEGA and SIGMA) for Nonmem simulation. NMsim() table for simulations. See argument file.ext and NMsim_VarCov’s argument ext.

  • New arguments to control seeds. NMsim can either use R’s set.seed before generating the seeds for Nonmem. Detailed control of the seeds, including how many to include and the distribution of the random sources in Nonmem, can be controlled using the seed.nm argument. This way, the user can add random processes to the estimated control stream. The actual Nonmem seed values can also be provided.

  • method.sim=NMsim_typical() has been replaced by argument typical=TRUE. This means typical subject simulations can now be combined with other simulations methods like NMsim_VarCov.

  • NMsim() now adds a column called sim which carries the name of the simulation defined by the name.sim argument.

  • Several checks for existence and consistency of files are implemented.

  • The native Nonmem execution method now also works for estimation.

  • pnm files are now saved with the model for transparency.

Bugfixes

  • Running rbind on results from NMsim would throw errors. Thanks to Simone Cassani for reporting this. Fixed.

  • Using other file name extensions than .mod on input control streams in combination with NMdataConf(file.mod) would make NMsim fail. Thanks to Brian Reilly for reporting. Fixed.

Other changes

  • NMsim_known() renamed to NMsim_EBE().

  • Generated control streams have been stripped off of the “NMsim_” prefix. These files are located in NMsim generated folders so the prefix was uninformative.

  • In case of multi-threaded (cluster) execution and something went wrong NMexec() used to write some output files from Nonmem in the current working directory. All these are now being written to the model execution directory for clarity and tidyness.

NMsim 0.1.0

CRAN release: 2024-02-22

For the first time NMsim works on Windows. There may still be some limitations but initial testing looks very promising. Make sure to set path.nonmem. See the configuration vignette on the website: NMsim-config.html

0.1.0 is also an important upgrade that solidifies the way NMsim reads results from simulations. In addition to important bug fixes, it allows for NMsim to wait on Nonmem to complete simulations - even when they are run on a cluster. This means even large simulations with NMsim can be integrated in scripts.

New features

  • Works on Windows - at least most features do.

  • NMsim() and NMreadSim() now have wait arguments which controls if they will wait for Nonmem to finish simulating. This will also work if jobs were sent to the cluster.

  • NMsim() respects the reuse.results argument. If TRUE it will use results file on the file system. This can be used in stead of putting NMsim() calls inside an if-statement to disable the simulation but read results on file.

  • NMsim() looks for a couple of features of the provided control streams that are known to be able to cause issues. Warnings will be issued if these are found.

  • addEVID2 has a new argument, EVID to specify what value the EVID column should have. It can be useful sometimes to use EVID=0 for simulation records.

Bugfixes

  • In some cases NMreadSim() would not get the path right to the simulation results leading to failures in reading simulation results. Fixed.

Other changes

  • Functions NMreadExt and NMreadPhi have been removed from NMsim. They live and are being maintained in the NMdata package. In NMsim, were deprecated and unmaintained functions.

NMsim 0.0.10

CRAN release: 2024-02-08

NMsim 0.0.9 had an unfortunate bug in NMreadSim() which has been fixed. That bugfix is difference between 0.0.9 and 0.0.10.

NMsim 0.0.9

CRAN release: 2024-02-07

NMsim 0.0.9 is almost identical to 0.0.8 but ensures compatibility with older R versions.

Bugfixes

  • In some cases NMreadSim would not be able to read and combine results from models that returned different data variables. Fixed.

NMsim 0.0.8

CRAN release: 2024-02-07

New features

  • NMsim 0.0.1 would generate an rds file with paths to simulation files and results for each model+data set simulated. This has been changed to now only generate one table per model. This makes it simpler to read simulation results in some cases.

  • NMreadSim should now be the best and only way for the user to read NMsim simulation results. It interprets rds files (which are the ones intended for reading), fst files, tables of NMsim runs, and NMsim results. This makes it less confusing what can be processed by NMreadSim and also it sometimes easier to generalize code reading simulation results. Also, NMsim now always reads results using NMreadSim. This has the advantage that an fst file will always be produced if NMsim waits to read the results.

  • NMreadSim has a new argument, check.time by default disabling checking whether a collected fst file is newer than the results files generated by NMsim. Normally, it’s a good thing to check this but some ways of sharing file files may not retain file modification times needed to check for this. NMsim will delete the fst files if it finds any so normally it should not be a problem to skip this check.

  • modify.model is the argument to use to modify the control stream after NMsim is done preparing the simulation. A couple of helper functions are available making it really easy to add contents (very commonly used) or modify contents.

  • NMsim now tries to reuse stored results if reuse.results=TRUE. It does so in a simple way - if they exist, they will be attempted read - so be careful to rerun simulations without this option if you change any arguments.

  • NMsim will by default add a DV column with NA values if DV is not in input data. Nonmem most often needs that column, and it is uninformative for simulations. Disable this feature by using auto.dv=FALSE.

  • The transform option has been integrated into the table of simulations created by NMsim(). This means even if the results are not read by NMsim (because the simulation is not executed or it is submitted to a cluster), the transformation will still be applied by NMreadSim() later.

  • NMsim()'s dir.sims and dir.res arguments can be controlled using NMdata::NMdataConf(). Often these two arguments are used all the time, so it’s convenient to be able to configure those once and for all in a script.

Bugfixes

  • NMreadSim was only able to read results if the current working directory was the same as when NMsim was executed. Now fixed.

  • In some cases NMsim would fail on models with multiple output tables when the table.vars argument was not used. Fixed.

  • NMsim’s sim.dir.from.scratch argument was not respected due to a simple bug, leading to dir.sims growing each time a simulation was rerun.

  • In case simulation data is a list of data sets NMsim would not order columns when order.columns was TRUE. Now fixed.

  • In case of lists of data sets, and the list element (data set) names included spaces, NMsim() would throw and error. Spaces in data set names are now replaced with under scores (“_“) to avoid that. It will often happen when data sets are split into lists using data.table::split.data.table() - which is an excellent way to do this, by the way.

  • Function simPopEtas() was not exported, so only available as NMsim:::simPopEtas(). Fixed.

NMsim 0.0.7

CRAN release: 2024-01-08

New features

  • Function simPopEtas() to generate a population from a model. The population can be saved as a phi file to be reused in subsequent simulations. The function is by mistake not exported in 0.0.7 so for now you must use NMsim:::simPopEtas() to use it.

  • Function NMreadSim() provides a very simple interface to reading simulation results. Especailly in cases where the simulation is being parallelized or otherwise spawns multiple Nonmem jobs, this is a useful feature.

  • A list of simulation data sets will now be simulated with separate Nonmem runs. This is an efficient way to parellelize large simulation runs.

NMsim 0.0.6

CRAN release: 2023-11-28

New features

  • Support for parallelization of simulations added when using PSN. It used to be possible to run multiple simulations simultaneously in separate threads. Now single simulation runs can be parallelized on sge type clusters (using qsub). See arguments sge and nc.

Bugfixes

  • A simple mistake would create problems in genPhiFile() when having more than 10 ETAs in a model. Now fixed.

NMsim 0.0.5

CRAN release: 2023-11-11

New features

  • Full support for models estimated with SAEM. Especially, simulation of “known” subjects, i.e. re-using emperical Bayes estimates, is slightly different with these models.

  • Experimental support for windows with PsN. dir.psn argument has to point to a directory where executables execute and update_inits are found. Thanks to Sjoerd Koopman for debugging and testing this. Hopefully in future versions, PsN will not be needed on Windows (like it is not needed on Linux).

  • The simulation method called NMsim_known now accepts other .phi files to use than the .phi file generated by the estimation run. This is useful if one wants to reuse subjects generated in a previous simulation.

Other/minor improvements

  • NMexec now also copies out the shk (shrinkage estimates) file after a run. The files that will by default be copied and reported next to the control streams are now xml, ext, cov, cor, coi, phi, shk - in addition to output table files and the archived input data of course.

NMsim 0.0.2

CRAN release: 2023-09-14

New features

  • NMsim supports type.sim="typical" which means all OMEGAS will be fixed to zero. This requires the ext file to be present.

  • Experimental support for simulation of estimated subjects using type.sim="known".