model.function {rxode2}

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.

Value

Model block with ini information included. ini must be called before model block

Author(s)

Matthew Fidler