| contrasts {stats} | R Documentation |
Get and Set Contrast Matrices
Description
Set and view the contrasts associated with a factor.
Usage
contrasts(x, contrasts = TRUE, sparse = FALSE)
contrasts(x, how.many = NULL) <- value
Arguments
x |
a factor or a logical variable. |
contrasts |
logical. See ‘Details’. |
sparse |
logical indicating if the result should be sparse
(of class |
how.many |
integer number indicating how many contrasts should be
made. Defaults to one
less than the number of levels of |
value |
either a numeric matrix (or a sparse or dense matrix of a
class extending |
Details
If contrasts are not set for a factor the default functions from
options("contrasts") are used.
A logical vector x is converted into a two-level factor with
levels c(FALSE, TRUE) (regardless of which levels occur in the
variable).
The argument contrasts is ignored if x has a matrix
contrasts attribute set. Otherwise if contrasts = TRUE
it is passed to a contrasts function such as
contr.treatment and if contrasts = FALSE
an identity matrix is returned. Suitable functions have a first
argument which is the character vector of levels, a named argument
contrasts (always called with contrasts = TRUE) and
optionally a logical argument sparse.
If value supplies more than how.many contrasts, the
first how.many are used. If too few are supplied, a suitable
contrast matrix is created by extending value after ensuring
its columns are contrasts (orthogonal to the constant term) and not
collinear.
References
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.
See Also
C,
contr.helmert,
contr.poly,
contr.sum,
contr.treatment;
glm,
aov,
lm.
Examples
utils::example(factor)
fff <- ff[, drop = TRUE] # reduce to 5 levels.
contrasts(fff) # treatment contrasts by default
contrasts(C(fff, sum))
contrasts(fff, contrasts = FALSE) # the 5x5 identity matrix
contrasts(fff) <- contr.sum(5); contrasts(fff) # set sum contrasts
contrasts(fff, 2) <- contr.sum(5); contrasts(fff) # set 2 contrasts
# supply 2 contrasts, compute 2 more to make full set of 4.
contrasts(fff) <- contr.sum(5)[, 1:2]; contrasts(fff)
## using sparse contrasts: % useful, once model.matrix() works with these :
ffs <- fff
contrasts(ffs) <- contr.sum(5, sparse = TRUE)[, 1:2]; contrasts(ffs)
stopifnot(all.equal(ffs, fff))
contrasts(ffs) <- contr.sum(5, sparse = TRUE); contrasts(ffs)