| model.matrix {stats} | R Documentation |
Construct Design Matrices
Description
model.matrix creates a design matrix.
Usage
model.matrix(object, ...)
## Default S3 method:
model.matrix(object, data = environment(object),
contrasts.arg = NULL, xlev = NULL, ...)
Arguments
object |
an object of an appropriate class. For the default method, a model formula or terms object. |
data |
a data frame created with |
contrasts.arg |
A list, whose entries are contrasts suitable for
input to the |
xlev |
to be used as argument of |
... |
further arguments passed to or from other methods. |
Details
model.matrix creates a design matrix from the description given
in terms(formula), using the data in data which must
contain columns with the same names as would be created by a call to
model.frame(formula) or, more precisely, by evaluating
attr(terms(formula), "variables"). There may be other columns
and the order is not important. If contrasts is specified it
overrides the default factor coding for that variable.
In interactions, the variable whose levels vary fastest is the first
one to appear in the formula (and not in the term), so in ~ a +
b + b:a the interaction will have a varying fastest.
By convention, if the response variable also appears on the right-hand side of the formula it is dropped (with a warning), although interactions involving the term are retained.
Value
The design matrix for a regression model with the specified formula and data.
References
Chambers, J. M. (1992) Data for models. Chapter 3 of Statistical Models in S eds J. M. Chambers and T. J. Hastie, Wadsworth \& Brooks/Cole.
See Also
model.frame, model.extract,
terms
Examples
ff <- log(Volume) ~ log(Height) + log(Girth)
str(m <- model.frame(ff, trees))
mat <- model.matrix(ff, m)
dd <- data.frame(a = gl(3,4), b = gl(4,1,12))# balanced 2-way
options("contrasts")
model.matrix(~ a + b, dd)
model.matrix(~ a + b, dd, contrasts = list(a="contr.sum"))
model.matrix(~ a + b, dd, contrasts = list(a="contr.sum", b="contr.poly"))
m.orth <- model.matrix(~a+b, dd, contrasts = list(a="contr.helmert"))
crossprod(m.orth)# m.orth is ALMOST orthogonal