engineParams: Specify engine parameters for model execution
In Certara.RsNLME: Pharmacometric Modeling

engineParams

R Documentation

Specify engine parameters for model execution

Description

Use to define extra engine parameters for model execution.

Usage

engineParams(
  model,
  sort = NULL,
  ODE = "MatrixExponent",
  rtolODE = 1e-06,
  atolODE = 1e-06,
  maxStepsODE = 50000,
  numIterations = 1000,
  method = NULL,
  stdErr = NULL,
  isCentralDiffStdErr = TRUE,
  stepSizeStdErr = NULL,
  numIntegratePtsAGQ = 1,
  numIterNonParametric = 0,
  allowSyntheticGradient = FALSE,
  numIterMAPNP = 0,
  numRepPCWRES = 0,
  stepSizeLinearize = 0.002,
  numDigitLaplacian = 7,
  numDigitBlup = 13,
  mapAssist = 0,
  iSample = 300,
  iAcceptRatio = 0.1,
  impDist = "Normal",
  tDOF = 4,
  numSampleSIR = 10,
  numBurnIn = 0,
  freezeOmega = FALSE,
  MCPEM = FALSE,
  runAllIterations = FALSE,
  scramble = "Owen",
  stepSizePartialDeriv = 1e-05,
  numTimeStepPartialDeriv = 20
)

Arguments

`model`	Model object
`sort`	Logical; Specifying whether or not to sort the input data by subject and time values. If `model@hasResetInfo = TRUE`, then `sort` must be set to `FALSE` (default); Otherwise, the default value for `sort` is `TRUE`.
`ODE`	Character; Specifying the solver used to numerically solve Ordinary Differential Equations (ODEs). Options are '"MatrixExponent"', '"Higham"', '"DVERK"', '"DOPRI5"', '"AutoDetect"', '"Stiff"'. See Details section.
`rtolODE`	Numeric; Specifying relative tolerance for the numerical ODE solver.
`atolODE`	Numeric; Specifying absolute tolerance for the numerical ODE solver.
`maxStepsODE`	Numeric; Specifying maximum number of allowable steps or function evaluations for the ODE solver.
`numIterations`	Numeric; Specifying maximum number of iterations for estimation.
`method`	Character; Specifying engine method for estimation. For population models, options are `"QRPEM"`, `"IT2S-EM"`, `"FOCE-LB"`, `"FO"`, `"FOCE-ELS"`, `"Laplacian"`, `"Naive-Pooled"`. While, for individual models, `"Naive-Pooled"` is the only option. Note: For population models, if `model` involves any discontinuous observed variable (e.g., count data) or BQL data, the default method is `"Laplacian"`; otherwise, the default method is `"FOCE-ELS"`.
`stdErr`	Character; Specifying method for standard error computations. For individual models, options are `"Hessian"` (default) and `"None"`; For population models with `method = "QRPEM"`, options are `"Fisher-Score"` (default) and `"None"`; For population models with `method = "IT2s-EM"`, the only option is `"None"`; For population models with `method` set to either `"FOCE-LB"`, `"FO"`, `"FOCE-ELS"`, `"Laplacian"`, or `"Naive-Pooled"`, options are `"Sandwich"` (default), `"Hessian"`, `"Fisher-Score"`, `"Auto-Detect"`, and `"None"`. Here `"None"` means that standard error calculations are not performed.
`isCentralDiffStdErr`	Logical; Default `TRUE` uses central difference for `stdErr` calculations. Set to `FALSE` for forward difference method.
`stepSizeStdErr`	Numeric; Specifying the step size used for `stdErr` calculations. If not specified, 0.01 is used for population models and 0.001 for individual models.
`numIntegratePtsAGQ`	Numeric; Specifying the number of integration points for adaptive Gaussian quadrature (AGQ) algorithm. Only applicable to population models with `method` set to either `"FOCE-ELS"` or `"Laplacian"`.
`numIterNonParametric`	Numeric; Specifying the number of iterations to perform non-parametric estimation. Only applicable to population models when `method` is not set to `Naive-Pooled`.
`allowSyntheticGradient`	Logical, Set to `TRUE` to use synthetic gradient during the estimation process. Only applicable to population models when `method` is not set to `Naive-Pooled`.
`numIterMAPNP`	Numeric; Specifying the number of iterations to perform Maximum A Posterior (MAP) initial Naive Pooling (NP) run before estimation. Only applicable to population models when `method` is not set to `Naive-Pooled`.
`numRepPCWRES`	Numeric; Specifying the number of replicates to generate the PCWRES after the simple estimation. Only applicable to population models when `method` is not set to `Naive-Pooled`.
`stepSizeLinearize`	Numeric; Specifying the step size used for numerical differentiation when linearizing the model function during the estimation process.
`numDigitLaplacian`	Numeric; Specifying the number of significant decimal digits for the Laplacian algorithm to use to reach convergence. Only applicable to population models.
`numDigitBlup`	Numeric; Specifying the number of significant decimal digits for the individual estimation to use to reach convergence. Only applicable to population models.
`mapAssist`	Numeric; Specifying the period used to perform MAP assistance (`mapAssist = 0` means that MAP assistance is not performed). Only applicable to population models with `method = "QRPEM"`.
`iSample`	Numeric; Specifying the number of samples. Only applicable to population models with `method = "QRPEM"`.
`iAcceptRatio`	Numeric; Specifying the acceptance ratio. Only applicable to population models with `method = "QRPEM"`.
`impDist`	Character; Specifying the distribution used for important sampling, and options are `"Normal"` (default), `"DoubleExponential"`, `"Direct"`, `"T"`, `"Mixture-2"`, `Mixture-3`. Only applicable to population models with `method = "QRPEM"`.
`tDOF`	Numeric; Specifing the degree of freedom (allowed value is between 3 and 30) for T distribution. Only applicable to population models with `method = "QRPEM"` and `impDist = "T"`.
`numSampleSIR`	Numeric; Specifying the number of samples per subject used in the Sampling Importance Re-Sampling (SIR) algorithm to determine the number of SIR samples taken from the empirical discrete distribution that approximates the target conditional distribution. Only applicable to population models with `method = "QRPEM"`.
`numBurnIn`	Numeric; Specifying the number of burn-in iterations to perform at startup to adjust certain internal parameters. Only applicable to population models with `method = "QRPEM"`.
`freezeOmega`	Logical; Set to `TRUE` to freeze Omega but not Theta for the number of iterations specified in the `numBurnIn`. Only applicable to population models with `method = "QRPEM"`.
`MCPEM`	Logical; Set to `TRUE` to use Monte-Carlo sampling instead of Quasi-Random. Only applicable to population models with `method = "QRPEM"`.
`runAllIterations`	Logical; Set to `TRUE` to execute all requested iterations specified in `numIterations`. Only applicable to population models with `method = "QRPEM"`.
`scramble`	Character; Specifying the quasi-random scrambling method to use, and options are `"Owen"`, `"Tezuka-Faur"`, or `"None"`. Only applicable to population models with `method = "QRPEM"`.
`stepSizePartialDeriv`	Numeric; Specifying the step size used to numerically calculate the partial derivatives of observed variables with respect to parameters. Only applicable to individual models.
`numTimeStepPartialDeriv`	Numeric; Specifying the number of time steps used to output the partial derivatives of observed variables with respect to parameters. Only applicable to individual models.

Details

Both '"DVERK"' and '"DOPRI5"' are non-stiff solvers. '"Higham"' is a matrix exponent based ODE solver which could be useful when overscaling issue should be avoided, i.e. the ratio between observed values and doses is too high or too low. '"AutoDetect"' represents LSODA solver implemenation, which solves the initial value problem for stiff or nonstiff systems of first order ordinary differential equations. '"Stiff"' is a LSODE (Livermore solver). It is best suited for stiff problems.