Fit the NLME metamodel
run_metamodel.RdUse for simple model execution given information contained in mmdl file.
Arguments
- mmdlfile
The metamodel file path; relative paths are acceptable.
- directoryToRun
The directory where the final results should be stored If
missing, the mmdlfile base directory is used.- nlme_hostPath
json file with host definition for model execution. Generated by Pirana application. Consider using
hostargument when running from R.- host
NlmeParallelHost()class instance.
Value
the results of fitmodel() run are returned if singular ESTARGS block is
provided; otherwise a list of fitmodel() and simmodel() results
are returned.
Details
If both nlme_hostPath and host specified, the former is used.
If nlme_hostPath is missing, host is used instead.
If both are missing, MPI local host with 4 threads is used for simple estimation
mode, multicore host is used for the others.
Multiple ESTARGS/SIMARGS are supported, they are applied for the model sequentially, the results of previous estimation are applied to the model before the next one. ESTARGS queue is executed first, SIMARGS queue is executed the second.
Examples
# \donttest{
mmdlfile <- system.file("extdata/mmdlNoTime/test.mmdl",
package = "Certara.RsNLME",
mustWork = TRUE)
directoryToRun <- file.path(tempdir(TRUE), "MmdlNoTimeTest")
# using default host
mmdlResults <- run_metamodel(mmdlfile = mmdlfile,
directoryToRun = directoryToRun)
#> TDL5 version: 25.7.1.1
#>
#> Status: OK
#> License expires: 2026-08-06
#> Refresh until: 2025-09-05 07:01:25
#> Current Date: 2025-08-06
#> Using MPI host with 4 cores
#>
#> NLME Job
#>
#> Compiling 1 of 1 NLME models
#> TDL5 version: 25.7.1.1
#>
#> Status: OK
#> License expires: 2026-08-06
#> Refresh until: 2025-09-05 07:01:25
#> Current Date: 2025-08-06
#> The model compiled
#>
#>
#> Iteration -2LL tvIC50 tvE0 nSubj nObs
#> 1 14879.64 25.2909 49.8759 200 2200
#> 2 13145.01 25.5952 49.7128 200 2200
#> 3 12271.68 26.0232 49.4550 200 2200
#> 4 12098.13 26.3378 49.2420 200 2200
#> 5 12074.18 26.5484 49.0834 200 2200
#> 6 12070.93 26.6742 48.9796 200 2200
#> 7 12066.05 26.9267 48.7684 200 2200
#> 8 12053.21 27.6780 48.1478 200 2200
#> 9 12027.70 29.3491 46.8241 200 2200
#> 10 12002.60 31.8775 45.1051 200 2200
#> 11 11978.92 31.7582 45.7785 200 2200
#> 12 11965.94 32.4204 46.3035 200 2200
#> 13 11963.47 31.6657 46.5080 200 2200
#> 14 11962.64 31.7099 46.4074 200 2200
#> 15 11960.48 31.5920 46.3043 200 2200
#> 16 11957.49 31.0233 46.4160 200 2200
#> 17 11951.58 29.3145 47.0941 200 2200
#> 18 11949.72 28.3482 47.7451 200 2200
#> 19 11949.24 28.3365 47.9320 200 2200
#> 20 11949.14 28.3490 47.9816 200 2200
#> 21 11949.07 28.3467 48.0175 200 2200
#> 22 11948.98 28.5314 48.0904 200 2200
#> 23 11948.59 28.4212 48.0874 200 2200
#> 24 11947.57 27.9670 48.1569 200 2200
#> 25 11946.62 28.0755 48.1358 200 2200
#> 26 11942.56 28.5058 47.9879 200 2200
#> 27 11942.41 28.5283 47.8889 200 2200
#> 28 11942.39 28.5655 47.8179 200 2200
#> 29 11942.39 28.5764 47.8029 200 2200
#>
#> Trying to generate job results...
#>
#> Generating Overall.csv
#> Generating EtaEta.csv
#> Generating EtaCov.csv
#> Generating EtaCovariate.csv
#> Generating EtaCovariateCat.csv
#> Generating StrCovariate.csv
#> Generating Eta.csv
#> Generating EtaStacked.csv
#> Generating bluptable.dat
#> Generating ConvergenceData.csv
#> Generating initest.csv
#> Generating omega.csv
#> Generating omega_stderr.csv
#> Generating theta.csv
#> Generating thetaCorrelation.csv
#> Generating thetaCovariance.csv
#> Generating Covariance.csv
#> Generating Residuals.csv
#> Generating posthoc.csv
#>
#> Finished summarizing results. Transferring data and loading the results...
#> Done generating job results.
# }