contrasts {stats} | R Documentation |
Set and view the contrasts associated with a factor.
contrasts(x, contrasts = TRUE, sparse = FALSE) contrasts(x, how.many = NULL) <- value
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 |
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.
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.
C
,
contr.helmert
,
contr.poly
,
contr.sum
,
contr.treatment
;
glm
,
aov
,
lm
.
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)