specify_EngineParams {Certara.RDarwin} | R Documentation |
Specify engine parameters for model execution
Description
Use to define extra engine parameters for model execution.
Usage
specify_EngineParams(
sort = FALSE,
ODE = c("MatrixExponent", "DVERK", "DOPRI5", "AutoDetect", "Stiff"),
rtolODE = 1e-06,
atolODE = 1e-06,
maxStepsODE = 50000L,
numIterations = 1000L,
method = c("FOCE-ELS", "QRPEM", "Laplacian", "Naive-Pooled", "FOCE-LB", "IT2S-EM",
"FO"),
stdErr = c("Sandwich", "Auto-Detect", "Hessian", "Fisher-Score", "None"),
isCentralDiffStdErr = TRUE,
stepSizeStdErr = 0.01,
numIntegratePtsAGQ = 1L,
numIterNonParametric = 0L,
allowSyntheticGradient = FALSE,
numIterMAPNP = 0L,
numRepPCWRES = 0L,
stepSizeLinearize = 0.002,
numDigitLaplacian = 7L,
numDigitBlup = 13L,
mapAssist = 0L,
iSample = 300L,
iAcceptRatio = 0.1,
impDist = c("Normal", "DoubleExponential", "Direct", "T", "Mixture-2", "Mixture-3"),
tDOF = 4L,
numSampleSIR = 10L,
numBurnIn = 0L,
freezeOmega = FALSE,
MCPEM = FALSE,
runAllIterations = FALSE,
scramble = c("Owen", "Tezuka-Faur", "None")
)
Arguments
sort |
Logical; Specifying whether or not to sort the input data by
subject and time values. Default is |
ODE |
Character; Specifying the solver used to numerically solve Ordinary Differential Equations (ODEs). Options are
Note: both |
rtolODE |
Numeric; Specifying relative tolerance for the ODE solver.
Not applicable when |
atolODE |
Numeric; Specifying absolute tolerance for the 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. Options are:
Note: if model involves any discontinuous observed variable (e.g., count
data) or BQL data, NLME will switch from default method |
stdErr |
Character; Specifying method for standard error computations. Options are:
Here |
isCentralDiffStdErr |
Logical; Default |
stepSizeStdErr |
Numeric; Specifying the step size used for |
numIntegratePtsAGQ |
Numeric; Specifying the number of integration
points for adaptive Gaussian quadrature (AGQ) algorithm. Only applicable to
models with |
numIterNonParametric |
Numeric; Specifying the number of iterations to
perform non-parametric estimation. Only applicable when |
allowSyntheticGradient |
Logical, Set to |
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 |
numRepPCWRES |
Numeric; Specifying the number of replicates to generate
the PCWRES after the simple estimation. Only applicable to population
models when |
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/ELS algorithm to use to reach convergence. |
numDigitBlup |
Numeric; Specifying the number of significant decimal digits for the individual estimation to use to reach convergence. |
mapAssist |
Numeric; Specifying the period used to perform MAP
assistance ( |
iSample |
Numeric; Specifying the number of samples. Only applicable
when |
iAcceptRatio |
Numeric; Specifying the acceptance ratio. Only applicable
when |
impDist |
Character; Specifying the distribution used for important sampling, and options are
Only applicable to the model with |
tDOF |
Numeric; Specifying the degree of freedom (allowed value is
between 3 and 30) for T distribution. Only applicable when |
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 |
numBurnIn |
Numeric; Specifying the number of burn-in iterations to
perform at startup to adjust certain internal parameters. Only applicable
to population models with |
freezeOmega |
Logical; Set to |
MCPEM |
Logical; Set to |
runAllIterations |
Logical; Set to |
scramble |
Character; Specifying the quasi-random scrambling method to use, and options are
Only applicable to population models with |
Value
Character
See Also
write_ModelTemplateTokens()
, specify_SimParams()
Examples
# default
EstArgs <- specify_EngineParams()
# QRPEM method
EstArgs <-
specify_EngineParams(
sort = TRUE,
ODE = "DVERK",
rtolODE = 1e-5,
atolODE = 1e-5,
maxStepsODE = 6000,
numIterations = 100,
method = "QRPEM",
numIterMAPNP = 3,
stdErr = "Fisher-Score",
isCentralDiffStdErr = FALSE,
iSample = 350,
impDist = "Mixture-2",
scramble = "Tezuka-Faur")