| effects {stats} | R Documentation |
Returns (orthogonal) effects from a fitted model, usually a linear
model. This is a generic function, but currently only has a methods for
objects inheriting from classes "lm" and "glm".
effects(object, ...) ## S3 method for class 'lm': effects(object, set.sign = FALSE, ...)
object |
an R object; typically, the result of a model fitting function
such as lm. |
set.sign |
logical. If TRUE, the sign of the effects
corresponding to coefficients in the model will be set to agree with the
signs of the corresponding coefficients, otherwise the sign is
arbitrary. |
... |
arguments passed to or from other methods. |
For a linear model fitted by lm or aov,
the effects are the uncorrelated single-degree-of-freedom values
obtained by projecting the data onto the successive orthogonal
subspaces generated by the QR decomposition during the fitting
process. The first r (the rank of the model) are associated with
coefficients and the remainder span the space of residuals (but are
not associated with particular residuals).
Empty models do not have effects.
A (named) numeric vector of the same length as
residuals, or a matrix if there were multiple responses
in the fitted model, in either case of class "coef".
The first r rows are labelled by the corresponding coefficients,
and the remaining rows are unlabelled. Note that in rank-deficient
models the “corresponding” coefficients will be in a different
order if pivoting occurred.
Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S. Wadsworth & Brooks/Cole.
y <- c(1:3,7,5) x <- c(1:3,6:7) ( ee <- effects(lm(y ~ x)) ) c(round(ee - effects(lm(y+10 ~ I(x-3.8))),3))# just the first is different