model.frame {base} | R Documentation |
model.frame
(a generic function) and its methods return a
data.frame
with the variables needed to use
formula
and any ...
arguments.
model.frame(formula, ...)
model.frame.default(formula, data = NULL,
subset = NULL, na.action = na.fail,
drop.unused.levels = FALSE, xlev = NULL, ...)
Methods for
lm glm aovlist
formula |
a model formula |
data |
|
subset |
a specification of the rows to be used. Defaults to all rows. |
na.action |
how |
drop.unused.levels |
should factors have unused levels dropped?
Defaults to |
xlev |
a named list of character vectors giving the full set of levels to be assumed for each factor. |
... |
further arguments such as |
Variables in the formula, subset
and in ...
are looked
for first in data
and then in the environment of
formula
: see the help for formula()
for further
details.
First all the variables needed are collected into a data frame.
Then subset
expression is evaluated, and it is is used as a row index to the data
frame. Then the na.action
function is applied to the data frame
(and may well add attributes). The levels of any factors in the data
frame are adjusted according to the drop.unused.levels
and
xlev
arguments.
A data.frame
containing the variables used in
formula
plus those specified ...
.
model.matrix
for the “design matrix”,
formula
for formulas and
expand.model.frame
for model.frame manipulation.
data(cars)
data.class(model.frame(dist ~ speed, data = cars))