| model.matrix {base} | R Documentation |
Construct Design Matrices
Description
model.matrix creates a design matrix.
Usage
model.matrix (object, ...)
model.matrix.lm(object, ...)
model.matrix.default(formula, data, contrasts.arg = NULL, xlev = NULL)
Arguments
formula |
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 |
x |
a model frame. |
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.
Value
The design matrix for a regression model with the specified formula and data.
References
Chambers, J. M. and Hastie, T. J. eds (1992) Statistical Models in S. Chapman & Hall, London.
See Also
model.frame, model.extract,
terms
Examples
data(trees)
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