Set and view the contrasts associated with a factor.
contrasts(x, contrasts = TRUE, sparse = FALSE) contrasts(x, how.many) <- value
- a factor or a logical variable.
- logical. See ‘Details’.
- logical indicating if the result should be sparse (of class
dgCMatrix), using package Matrix.
- How many contrasts should be made. Defaults to one less than the number of levels of
x. This need not be the same as the number of columns of
- either a numeric matrix (or a sparse or dense matrix of a class extending
dMatrixfrom package Matrix) whose columns give coefficients for contrasts in the levels of
x, or the (quoted) name of a function which computes such matrices.
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).
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 from R 2.10.0 a logical argument
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.
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)
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