| effects {stats} | R Documentation |
Effects from Fitted Model
Description
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".
Usage
effects(object, ...)
## S3 method for class 'lm'
effects(object, set.sign = FALSE, ...)
Arguments
object |
an R object; typically, the result of a model fitting function
such as |
set.sign |
logical. If |
... |
arguments passed to or from other methods. |
Details
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.
Value
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.
References
Chambers, J. M. and Hastie, T. J. (1992) Statistical Models in S. Wadsworth & Brooks/Cole.
See Also
Examples
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