contrasts
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) <- 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 | 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)
Copyright (©) 1999–2012 R Foundation for Statistical Computing.
Licensed under the GNU General Public License.