The generic function
formula and its specific methods provide a way of extracting formulae which have been included in other objects.
as.formula is almost identical, additionally preserving attributes when
object already inherits from
formula(x, ...) as.formula(object, env = parent.frame()) ## S3 method for class 'formula': print((x, showEnv = !identical(e, .GlobalEnv), ...))
- x, object
- R object.
- further arguments passed to or from other methods.
- the environment to associate with the result, if not already a formula.
- logical indicating if the environment should be printed as well.
The models fit by, e.g., the
glm functions are specified in a compact symbolic form. The
~ operator is basic in the formation of such models. An expression of the form
y ~ model is interpreted as a specification that the response
y is modelled by a linear predictor specified symbolically by
model. Such a model consists of a series of terms separated by
+ operators. The terms themselves consist of variable and factor names separated by
: operators. Such a term is interpreted as the interaction of all the variables and factors appearing in the term.
In addition to
:, a number of other operators are useful in model formulae. The
* operator denotes factor crossing:
a*b interpreted as
^ operator indicates crossing to the specified degree. For example
(a+b+c)^2 is identical to
(a+b+c)*(a+b+c) which in turn expands to a formula containing the main effects for
c together with their second-order interactions. The
%in% operator indicates that the terms on its left are nested within those on the right. For example
a + b %in% a expands to the formula
a + a:b. The
- operator removes the specified terms, so that
(a+b+c)^2 - a:b is identical to
a + b + c + b:c + a:c. It can also used to remove the intercept term: when fitting a linear model
y ~ x - 1 specifies a line through the origin. A model with no intercept can be also specified as
y ~ x + 0 or
y ~ 0 + x.
While formulae usually involve just variable and factor names, they can also involve arithmetic expressions. The formula
log(y) ~ a + log(x) is quite legal. When such arithmetic expressions involve operators which are also used symbolically in model formulae, there can be confusion between arithmetic and symbolic operator use.
To avoid this confusion, the function
I() can be used to bracket those portions of a model formula where the operators are used in their arithmetic sense. For example, in the formula
y ~ a + I(b+c), the term
b+c is to be interpreted as the sum of
Variable names can be quoted by backticks
`like this` in formulae, although there is no guarantee that all code using formulae will accept such non-syntactic names.
Most model-fitting functions accept formulae with right-hand-side including the function
offset to indicate terms with a fixed coefficient of one. Some functions accept other ‘specials’ such as
cluster (see the
specials argument of
There are two special interpretations of
. in a formula. The usual one is in the context of a
data argument of model fitting functions and means ‘all columns not otherwise in the formula’: see
terms.formula. In the context of
update.formula, only, it means ‘what was previously in this part of the formula’.
formula is called on a fitted model object, either a specific method is used (such as that for class
"nls") or the default method. The default first looks for a
"formula" component of the object (and evaluates it), then a
"terms" component, then a
formula parameter of the call (and evaluates its value) and finally a
There is a
formula method for data frames. If there is only one column this forms the RHS with an empty LHS. For more columns, the first column is the LHS of the formula and the remaining columns separated by
+ form the RHS.
All the functions above produce an object of class
"formula" which contains a symbolic model formula.
A formula object has an associated environment, and this environment (rather than the parent environment) is used by
model.frame to evaluate variables that are not found in the supplied
Formulas created with the
~ operator use the environment in which they were created. Formulas created with
as.formula will use the
env argument for their environment.
Chambers, J. M. and Hastie, T. J. (1992) Statistical models. Chapter 2 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth & Brooks/Cole.
class(fo <- y ~ x1*x2) # "formula" fo typeof(fo) # R internal : "language" terms(fo) environment(fo) environment(as.formula("y ~ x")) environment(as.formula("y ~ x", env = new.env())) ## Create a formula for a model with a large number of variables: xnam <- paste0("x", 1:25) (fmla <- as.formula(paste("y ~ ", paste(xnam, collapse= "+"))))
Documentation reproduced from R 3.0.2. License: GPL-2.