an optional data frame containing the variables in the model.
If not found in data, the variables are taken from
frame, by default the environment from which
ModelEnvFormula is called.
subset
an optional vector specifying a subset of observations to
be used in the fitting process.
na.action
a function which indicates what should happen when the data
contain NA's.
frame
an optional environment formula is evaluated in.
enclos
specifies the enclosure passed to eval for
evaluating the model frame. The model frame is evaluated in
envir = frame with enclos = enclos,
see eval.
other
an optional named list of additional formulae.
designMatrix
a logical indicating whether the design matrix
defined by the right hand side of formula
should be computed.
responseMatrix
a logical indicating whether the design matrix
defined by the left hand side of formula
should be computed.
setHook
a list of functions to MEapply every
time set is called on the object.
...
additional arguments for be passed to function, for example
contrast.arg to model.matrix.
Details
This function is an attempt to provide a flexible infrastucture for the
implementation of classical formula based interfaces. The arguments
formula, data, subset and na.action are well
known and are defined in the same way as in lm, for example.
ModelEnvFormula returns an object of class
ModelEnvFormula-class - a high level object for storing
data improving upon the capabilities of data.frames.
Value
An object of class ModelEnvFormula-class.
Examples
### the `usual' interface
data(iris)
mf <- ModelEnvFormula(Species ~ ., data = iris)
mf
### extract data from the ModelEnv object
summary(mf@get("response"))
summary(mf@get("input"))
dim(mf@get("designMatrix"))
### contrasts
mf <- ModelEnvFormula(Petal.Width ~ Species, data = iris,
contrasts.arg = list(Species = contr.treatment))
attr(mf@get("designMatrix"), "contrasts")
mf <- ModelEnvFormula(Petal.Width ~ Species, data = iris,
contrasts.arg = list(Species = contr.sum))
attr(mf@get("designMatrix"), "contrasts")
### additional formulae
mf <- ModelEnvFormula(Petal.Width ~ Species, data = iris,
other = list(pl = ~ Petal.Length))
ls(mf@env)
identical(mf@get("pl")[[1]], iris[["Petal.Length"]])