model: Model block for rxode2/nlmixr models
In rxode2: Facilities for Simulating from ODE-Based Models

model.function

R Documentation

Model block for rxode2/nlmixr models

Description

Model block for rxode2/nlmixr models

Usage

## S3 method for class ''function''
model(
  x,
  ...,
  append = NULL,
  auto = getOption("rxode2.autoVarPiping", TRUE),
  cov = NULL,
  envir = parent.frame()
)

## S3 method for class 'rxUi'
model(
  x,
  ...,
  append = NULL,
  auto = getOption("rxode2.autoVarPiping", TRUE),
  cov = NULL,
  envir = parent.frame()
)

## S3 method for class 'rxode2'
model(
  x,
  ...,
  append = NULL,
  auto = getOption("rxode2.autoVarPiping", TRUE),
  cov = NULL,
  envir = parent.frame()
)

## S3 method for class 'rxModelVars'
model(
  x,
  ...,
  append = NULL,
  auto = getOption("rxode2.autoVarPiping", TRUE),
  cov = NULL,
  envir = parent.frame()
)

model(
  x,
  ...,
  append = FALSE,
  auto = getOption("rxode2.autoVarPiping", TRUE),
  cov = NULL,
  envir = parent.frame()
)

## Default S3 method:
model(x, ..., append = FALSE, cov = NULL, envir = parent.frame())

Arguments

`x`	model expression
`...`	Other arguments
`append`	This is a boolean to determine if the lines are appended in piping. The possible values for this is: `TRUE` which is when the lines are appended to the model instead of replaced `FALSE` when the lines are replaced in the model (default) `NA` is when the lines are pre-pended to the model instead of replaced `⁠lhs expression⁠`, which will append the lines after the last observed line of the expression `lhs`
`auto`	This boolean tells if piping automatically selects the parameters should be characterized as a population parameter, between subject variability, or a covariate. When `TRUE` this automatic selection occurs. When `FALSE` this automatic selection is turned off and everything is added as a covariate (which can be promoted to a parameter with the `ini` statement). By default this is `TRUE`, but it can be changed by `options(rxode2.autoVarPiping=FALSE)`.
`cov`	is a character vector of variables that should be assumed to be covariates. This will override automatic promotion to a population parameter estimate (or an eta)
`envir`	the `environment` in which unevaluated model expressions is to be evaluated. May also be `NULL`, a list, a data frame, a pairlist or an integer as specified to `sys.call`.