NONMEM estimation control

Usage

nonmemControl(
  est = c("focei", "imp", "its", "posthoc"),
  advanOde = c("advan13", "advan8", "advan6"),
  linCmt = c("advan", "ode"),
  prune = "auto",
  cov = c("r,s", "r", "s", ""),
  maxeval = 1e+05,
  tol = 6,
  atol = 12,
  sstol = 6,
  ssatol = 12,
  sigl = 12,
  sigdig = 3,
  print = 1,
  extension = getOption("babelmixr2.nmModelExtension", ".nmctl"),
  outputExtension = getOption("babelmixr2.nmOutputExtension", ".lst"),
  runCommand = getOption("babelmixr2.nonmem", ""),
  iniSigDig = 5,
  protectZeros = FALSE,
  protect = getOption("babelmixr2.nmProtect", TRUE),
  muRef = TRUE,
  addProp = c("combined2", "combined1"),
  rxControl = NULL,
  sumProd = FALSE,
  optExpression = TRUE,
  calcTables = TRUE,
  compress = TRUE,
  ci = 0.95,
  sigdigTable = NULL,
  readRounding = FALSE,
  readBadOpt = FALSE,
  niter = 100L,
  isample = 1000L,
  iaccept = 0.4,
  iscaleMin = 0.1,
  iscaleMax = 10,
  df = 4,
  seed = 14456,
  mapiter = 1,
  mapinter = 0,
  noabort = TRUE,
  modelName = NULL,
  muRefCovAlg = TRUE,
  run = TRUE,
  ...
)

Arguments

est

NONMEM estimation method: "focei" (METHOD=1 INTER), "imp" (importance sampling, METHOD=IMP INTERACTION), "its" (iterative two stage, METHOD=ITS INTERACTION) or "posthoc" (METHOD=0 MAXEVALS=0 POSTHOC)

advanOde

The ODE solving method for NONMEM

linCmt

How a linCmt() model is written for NONMEM: "advan" uses NONMEM's closed-form solutions (ADVAN1-ADVAN4, ADVAN11 or ADVAN12 with TRANS1 micro-constants) when the model allows it and otherwise translates the model to ODEs; "ode" always translates the model to ODEs (with rxode2::linToOde()) and solves it with advanOde

prune

How if/else statements are written for NONMEM: "auto" (default) writes a model whose if blocks are simple (no else, else if, nesting or ifelse()) as NONMEM IF blocks, and otherwise prunes the if/else branches; TRUE always prunes a model with if/else statements and FALSE never prunes (so NONMEM can only use simple if blocks). Pruning uses rxode2's branch pruning (the same pruning nlmixr2 uses for its symbolic derivatives), which writes each branch as an arithmetic expression; this allows the nested if/else if/else statements NONMEM models cannot otherwise use. A pruned fit contains the pruned model.

cov

The NONMEM covariance method; "" skips the covariance step

maxeval

NONMEM's maxeval (for non posthoc methods)

tol

NONMEM tolerance for ODE solving advan

atol

NONMEM absolute tolerance for ODE solving

sstol

NONMEM tolerance for steady state ODE solving

ssatol

NONMEM absolute tolerance for steady state ODE solving

sigl

NONMEM sigl estimation option

sigdig

the significant digits for NONMEM

print

The print number for NONMEM

extension

NONMEM file extensions

outputExtension

Extension to use for the NONMEM output listing

runCommand

Command to run NONMEM (typically the path to "nmfe75") or a function. See the details for more information.

iniSigDig

How many significant digits are printed in $THETA and $OMEGA when the estimate is zero. Also controls the zero protection numbers

protectZeros

Add babelmixr2's own code to protect divide by zero (and the domains of log(), sqrt() and similar functions) in the control stream. This is only used when protect=FALSE (for example with NONMEM before 7.4); with protect=TRUE, NONMEM's $ABBR PROTECT protects these instead

protect

Add $ABBR PROTECT to the control stream so NM-TRAN replaces LOG, EXP, SQRT, division and powers with NONMEM's protected functions (PLOG, PEXP, PSQRT, PDZ); this requires NONMEM 7.4 or later. The default comes from the babelmixr2.nmProtect option, which is TRUE when unset

muRef

Automatically mu-reference the control stream

addProp, sumProd, optExpression, calcTables, compress, ci, sigdigTable

Passed to nlmixr2est::foceiControl

rxControl

Options to pass to rxode2::rxControl for simulations

readRounding

Try to read NONMEM output when NONMEM terminated due to rounding errors

readBadOpt

Try to read NONMEM output when NONMEM terminated due to an apparent failed optimization

niter

number of iterations in NONMEM estimation methods

isample

Isample argument for NONMEM IMP estimation method

iaccept

Iaccept for NONMEM IMP estimation method

iscaleMin

parameter for IMP NONMEM method (ISCALE_MIN)

iscaleMax

parameter for IMP NONMEM method (ISCALE_MAX)

df

degrees of freedom for IMP method

seed

is the seed for NONMEM methods

mapiter

the number of map iterations for IMP method

mapinter

is the MAPINTER parameter for the IMP method

noabort

Add the NOABORT option for $EST

modelName

Model name used to generate the NONMEM output. If NULL try to infer from the model name (could be x if not clear). Otherwise use this character for outputs.

muRefCovAlg

This controls if algebraic expressions that can be mu-referenced are treated as mu-referenced covariates by:

1. Creating a internal data-variable `nlmixrMuDerCov#` for each algebraic mu-referenced expression

2. Change the algebraic expression to `nlmixrMuDerCov# * mu_cov_theta`

3. Use the internal mu-referenced covariate for saem

4. After optimization is completed, replace `model()` with old `model()` expression

5. Remove `nlmixrMuDerCov#` from nlmix2 output

In general, these covariates should be more accurate since it changes the system to a linear compartment model. Therefore, by default this is `TRUE`.

run

Should NONMEM be run (and the files imported to nlmixr2); default is TRUE, but FALSE will simply create the NONMEM control stream and data file.

...

optional genRxControl argument controlling automatic rxControl generation.

Value

babelmixr2 control option for generating NONMEM control stream and reading it back into babelmixr2/nlmixr2

Details

If runCommand is given as a string, it will be called with the system() command like:

runCommand controlFile outputFile.

For example, if runCommand="'/path/to/nmfe75'" then the command line used would look like the following:

'/path/to/nmfe75' one.cmt.nmctl one.cmt.lst

If runCommand is given as a function, it will be called as FUN(ctl, directory, ui) to run NONMEM. This allows you to run NONMEM in any way that you may need, as long as you can write it in R. babelmixr2 will wait for the function to return before proceeding.

If runCommand is NA, nlmixr() will stop after writing the model files and without starting NONMEM.

Author

Matthew L. Fidler

Examples


nonmemControl()
#> $est
#> [1] "focei"
#> 
#> $cov
#> [1] "r,s"
#> 
#> $advanOde
#> [1] "advan13"
#> 
#> $linCmt
#> [1] "advan"
#> 
#> $prune
#> [1] "auto"
#> 
#> $maxeval
#> [1] 1e+05
#> 
#> $print
#> [1] 1
#> 
#> $noabort
#> [1] TRUE
#> 
#> $iniSigDig
#> [1] 5
#> 
#> $tol
#> [1] 6
#> 
#> $atol
#> [1] 12
#> 
#> $sstol
#> [1] 6
#> 
#> $ssatol
#> [1] 12
#> 
#> $sigl
#> [1] 12
#> 
#> $muRef
#> [1] TRUE
#> 
#> $sigdig
#> [1] 3
#> 
#> $protectZeros
#> [1] FALSE
#> 
#> $protect
#> [1] TRUE
#> 
#> $runCommand
#> [1] ""
#> 
#> $outputExtension
#> [1] ".lst"
#> 
#> $addProp
#> [1] "combined2"
#> 
#> $rxControl
#> $scale
#> NULL
#> 
#> $method
#> liblsoda 
#>        2 
#> 
#> $atol
#> [1] 1e-12
#> 
#> $rtol
#> [1] 1e-06
#> 
#> $maxsteps
#> [1] 70000
#> 
#> $hmin
#> [1] 0
#> 
#> $hmax
#> [1] NA
#> 
#> $hini
#> [1] 0
#> 
#> $maxordn
#> [1] 12
#> 
#> $maxords
#> [1] 5
#> 
#> $covsInterpolation
#> nocb 
#>    2 
#> 
#> $addCov
#> [1] TRUE
#> 
#> $returnType
#> rxSolve 
#>       0 
#> 
#> $sigma
#> NULL
#> 
#> $sigmaDf
#> NULL
#> 
#> $nCoresRV
#> [1] 1
#> 
#> $sigmaIsChol
#> [1] FALSE
#> 
#> $sigmaSeparation
#> [1] "auto"
#> 
#> $sigmaXform
#> identity 
#>        4 
#> 
#> $nDisplayProgress
#> [1] 10000
#> 
#> $amountUnits
#> [1] NA
#> 
#> $timeUnits
#> [1] "hours"
#> 
#> $addDosing
#> [1] FALSE
#> 
#> $stateTrim
#> [1] Inf
#> 
#> $updateObject
#> [1] FALSE
#> 
#> $omega
#> NULL
#> 
#> $omegaDf
#> NULL
#> 
#> $omegaIsChol
#> [1] FALSE
#> 
#> $omegaSeparation
#> [1] "auto"
#> 
#> $omegaXform
#> variance 
#>        6 
#> 
#> $nSub
#> [1] 1
#> 
#> $thetaMat
#> NULL
#> 
#> $thetaDf
#> NULL
#> 
#> $thetaIsChol
#> [1] FALSE
#> 
#> $nStud
#> [1] 1
#> 
#> $dfSub
#> [1] 0
#> 
#> $dfObs
#> [1] 0
#> 
#> $seed
#> NULL
#> 
#> $nsim
#> NULL
#> 
#> $minSS
#> [1] 10
#> 
#> $maxSS
#> [1] 10000
#> 
#> $strictSS
#> [1] 1
#> 
#> $infSSstep
#> [1] 12
#> 
#> $istateReset
#> [1] TRUE
#> 
#> $subsetNonmem
#> [1] TRUE
#> 
#> $hmaxSd
#> [1] 0
#> 
#> $maxAtolRtolFactor
#> [1] 0.1
#> 
#> $from
#> NULL
#> 
#> $to
#> NULL
#> 
#> $by
#> NULL
#> 
#> $length.out
#> NULL
#> 
#> $iCov
#> NULL
#> 
#> $keep
#> NULL
#> 
#> $keepF
#> character(0)
#> 
#> $drop
#> NULL
#> 
#> $warnDrop
#> [1] TRUE
#> 
#> $omegaLower
#> [1] -Inf
#> 
#> $omegaUpper
#> [1] Inf
#> 
#> $sigmaLower
#> [1] -Inf
#> 
#> $sigmaUpper
#> [1] Inf
#> 
#> $thetaLower
#> [1] -Inf
#> 
#> $thetaUpper
#> [1] Inf
#> 
#> $indLinPhiM
#> [1] 0
#> 
#> $indLinPhiTol
#> [1] 1e-07
#> 
#> $indLinMatExpType
#> Al-Mohy 
#>       3 
#> 
#> $indLinMatExpOrder
#> [1] 6
#> 
#> $idFactor
#> [1] TRUE
#> 
#> $mxhnil
#> [1] 0
#> 
#> $hmxi
#> [1] 0
#> 
#> $warnIdSort
#> [1] TRUE
#> 
#> $ssAtol
#> [1] 1e-12
#> 
#> $ssRtol
#> [1] 1e-06
#> 
#> $safeZero
#> [1] 0
#> 
#> $sumType
#> pairwise 
#>        1 
#> 
#> $prodType
#> long double 
#>           1 
#> 
#> $resample
#> NULL
#> 
#> $resampleID
#> [1] TRUE
#> 
#> $maxwhile
#> [1] 100000
#> 
#> $cores
#> [1] 0
#> 
#> $atolSens
#> [1] 1e-08
#> 
#> $rtolSens
#> [1] 1e-06
#> 
#> $ssAtolSens
#> [1] 1e-08
#> 
#> $ssRtolSens
#> [1] 1e-06
#> 
#> $simVariability
#> [1] NA
#> 
#> $nLlikAlloc
#> NULL
#> 
#> $useStdPow
#> [1] 0
#> 
#> $naTimeHandle
#> ignore 
#>      1 
#> 
#> $addlKeepsCov
#> [1] FALSE
#> 
#> $addlDropSs
#> [1] TRUE
#> 
#> $ssAtDoseTime
#> [1] TRUE
#> 
#> $ss2cancelAllPending
#> [1] FALSE
#> 
#> $naInterpolation
#> locf 
#>    1 
#> 
#> $keepInterpolation
#> na 
#>  2 
#> 
#> $safeLog
#> [1] 1
#> 
#> $safePow
#> [1] 1
#> 
#> $ssSolved
#> [1] TRUE
#> 
#> $linCmtSensType
#> auto 
#>  100 
#> 
#> $linCmtSensH
#> [1] 1e-04
#> 
#> $linCmtGillFtol
#> [1] 0
#> 
#> $linCmtGillK
#> [1] 20
#> 
#> $linCmtGillStep
#> [1] 4
#> 
#> $linCmtGillRtol
#> [1] 1.490116e-08
#> 
#> $linCmtShiErr
#> [1] 1.490116e-08
#> 
#> $linCmtShiMax
#> [1] 20
#> 
#> $linCmtScale
#> [1] 0 0 0 0 0 0 0
#> 
#> $linCmtHcmt
#> [1] 1
#> 
#> $linCmtHmeanI
#> geometric 
#>         2 
#> 
#> $linCmtHmeanO
#> geometric 
#>         2 
#> 
#> $linCmtSuspect
#> [1] 1e-06
#> 
#> $linCmtForwardMax
#> [1] 2
#> 
#> $indOwnAlloc
#> [1] -1
#> 
#> $maxExtra
#> [1] 1000
#> 
#> $tolFactor
#> NULL
#> 
#> $serializeFile
#> NULL
#> 
#> $dense
#> [1] FALSE
#> 
#> $cvodeLinSolver
#> dense 
#>     1 
#> 
#> $stiff2
#> [1] 0
#> 
#> $autoSwitchMaxStiff
#> [1] 10
#> 
#> $autoSwitchMaxNonstiff
#> [1] 3
#> 
#> $autoSwitchStiffFirst
#> [1] 0
#> 
#> $autoSwitchNonstifftol
#> [1] 0.9
#> 
#> $autoSwitchStifftol
#> [1] 0.9
#> 
#> $autoSwitchDtfac
#> [1] 2
#> 
#> $autoSwitchSwitchMax
#> [1] 5
#> 
#> $useLinCmt
#> [1] FALSE
#> 
#> $file
#> NULL
#> 
#> $chunkSize
#> NULL
#> 
#> $parallel
#> [1] 0
#> 
#> $.zeros
#> NULL
#> 
#> $zeroVarParamHandle
#> [1] "warn"
#> 
#> $indLinStepSearch
#> [1] 1
#> 
#> $indLinMaxIter
#> [1] 20
#> 
#> $indLinRichardson
#> [1] 2
#> 
#> $indLinIteration
#> [1] 3
#> 
#> $indLinJac
#> [1] 0
#> 
#> $indLinForcing
#> [1] 1
#> 
#> $usePrior
#> [1] NA
#> 
#> $priorPdRetry
#> [1] 10
#> 
#> $priorOmega
#> NULL
#> 
#> $priorOmegaEl
#> NULL
#> 
#> $priorSigmaEl
#> NULL
#> 
#> $linCmtSensPhi
#> [1] 2
#> 
#> $nonmem
#> [1] FALSE
#> 
#> attr(,"class")
#> [1] "rxControl"
#> 
#> $sumProd
#> [1] FALSE
#> 
#> $optExpression
#> [1] TRUE
#> 
#> $calcTables
#> [1] TRUE
#> 
#> $compress
#> [1] TRUE
#> 
#> $ci
#> [1] 0.95
#> 
#> $sigdigTable
#> NULL
#> 
#> $readRounding
#> [1] FALSE
#> 
#> $readBadOpt
#> [1] FALSE
#> 
#> $genRxControl
#> [1] TRUE
#> 
#> $niter
#> [1] 100
#> 
#> $isample
#> [1] 1000
#> 
#> $iaccept
#> [1] 0.4
#> 
#> $iscaleMin
#> [1] 0.1
#> 
#> $iscaleMax
#> [1] 10
#> 
#> $df
#> [1] 4
#> 
#> $seed
#> [1] 14456
#> 
#> $mapiter
#> [1] 1
#> 
#> $modelName
#> NULL
#> 
#> $muRefCovAlg
#> [1] TRUE
#> 
#> $run
#> [1] TRUE
#> 
#> attr(,"class")
#> [1] "nonmemControl"