Executes an NLME Bootstrap

Method to execute an NLME Bootstrap

Usage

bootstrap(
  model,
  hostPlatform = NULL,
  params,
  bootParams,
  runInBackground = FALSE,
  ...
)

Arguments

model

PK/PD model class object.

hostPlatform

Host definition for model execution. See hostParams. If missing, multicore local host with 4 threads is used.

params

Engine parameters. See engineParams. If missing, default parameters generated by engineParams(model) are used.

bootParams

Bootstrap parameters. See BootstrapParams. If missing, default parameters generated by BootstrapParams() are used.

runInBackground

Set to TRUE to run in background and return prompt.

...

Additional class initializer arguments for BootstrapParams or hostParams, or arguments available inside engineParams functions. If engineParams arguments are supplied through both params argument and additional argument (i.e., ellipsis), then the arguments in params will be ignored and only the additional arguments will be used with warning. If hostParams arguments are supplied through both hostPlatform argument and additional argument, then its values will be overridden by additional arguments. In addition, if BootstrapParams arguments are supplied through both bootParams argument and additional argument, then its slots will be overridden by additional arguments.

Value

if runInBackground = FALSE, a list is returned with bootstrap results, i.e. "BootOverall", "BootTheta", "BootOmega", "BootOmegaStderr", "BootVarCoVar" comma separated files. Otherwise the BootNlmeJob class object is returned.

See also

hostParams, engineParams, BootstrapParams

Examples

if (FALSE) { # \dontrun{
input_data <- pkData

model <-
  pkmodel(
    numCompartments = 2,
    data = input_data,
    ID = "Subject",
    Time = "Act_Time",
    A1 = "Amount",
    CObs = "Conc"
  )

# multicore
multicoreHost <- hostParams(
  parallelMethod = "Multicore",
  hostName = "local_multicore",
  numCores = 4
)

bootstrapdf <- bootstrap(model,
  hostPlatform = multicoreHost,
  params = engineParams(model),
  numReplicates = 5,
  randomNumSeed = 1234,
  runInBackground = FALSE
)
} # }