The R Project SVN R

\name{model.matrix}
\alias{model.matrix}
\alias{model.matrix.default}
\alias{model.matrix.lm}
%\alias{model.matrix.lm.null}
%\alias{model.matrix.glm.null}
\title{Construct Design Matrices}
\usage{
model.matrix(object, \dots)

\method{model.matrix}{default}(object, data = environment(object),
             contrasts.arg = NULL, xlev = NULL, \dots)
}
\arguments{
  \item{object}{an object of an appropriate class.  For the default
    method, a model formula or terms object.}
  \item{data}{a data frame created with \code{\link{model.frame}}.  If
    another sort of object, \code{model.frame} is called first.}
  \item{contrasts.arg}{A list, whose entries are contrasts suitable for
    input to the \code{\link{contrasts}} replacement function and
    whose names are the names of columns of \code{data} containing
    \code{\link{factor}}s.}
  \item{xlev}{to be used as argument of \code{\link{model.frame}} if
    \code{data} has no \code{"terms"} attribute.}
  \item{\dots}{further arguments passed to or from other methods.}
}
\description{
  \code{model.matrix} creates a design matrix.
}
\details{
  \code{model.matrix} creates a design matrix from the description given
  in \code{terms(object)}, using the data in \code{data} which must
  contain variables with the same names as would be created by a call to
  \code{model.frame(object)} or, more precisely, by evaluating
  \code{attr(terms(object), "variables")}.  If it is a data frame,
  there may be other columns and the order of columns is not important.
  Any character variables are coerced to factors, with a warning.
  After coercion, all the variables used in RHD of the formula must be
  logical, integer, numeric or factor.
  
  If \code{contrasts.arg} is specified for a factor it overrides the
  default factor coding for that variable and any \code{"contrasts"}
  attribute set by \code{\link{C}} or \code{\link{contrasts}}.

  In an interaction term, the variable whose levels vary fastest is the
  first one to appear in the formula (and not in the term), so in
  \code{~ a + b + b:a} the interaction will have \code{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.

  There is an attribute \code{"assign"}, an integer vector with an entry
  for each column in the matrix giving the term in the formula which
  gave rise to the column.  Value \code{0} corresponds to the intercept
  (if any), and positive values to terms in the order given by the
  \code{terms.labels} attribute of the \code{terms} structure
  corresponding to \code{object}.
  
  If there are any factors in terms in the model, there is an attribute
  \code{"contrasts"}, a named list with an entry for each factor.  This
  specifies the contrasts that would be used in terms in which the
  factor is coded by contrasts (in some terms dummy coding may be used),
  either as a character vector naming a function or as a numeric matrix.
}
\references{
  Chambers, J. M. (1992)
  \emph{Data for models.}
  Chapter 3 of \emph{Statistical Models in S}
  eds J. M. Chambers and T. J. Hastie, Wadsworth \& Brooks/Cole.
}
\seealso{
  \code{\link{model.frame}}, \code{\link{model.extract}},
  \code{\link{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
}
\keyword{models}