Box-Cox Transformations for Linear Models
DESCRIPTION:
Computes and optionally plots profile log-likelihoods for the
parameter of the Box-Cox power transformation.
USAGE:
boxcox(object, lambda, plotit, interp, eps, xlab, ylab, ...)
REQUIRED ARGUMENTS:
- object
-
a formula or fitted model object. Currently only
lm
and
aov
objects are handled.
OPTIONAL ARGUMENTS:
- lambda
-
vector of values of
lambda
--- default
(-2, 2) in steps of 0.1.
- plotit
-
logical which controls whether the result should be plotted.
Default to
true
if a graphics device is currently open.
- interp
-
logical which controls whether spline interpolation is used. Default
is
T
if plotting with
lambda
of length less than 100.
- eps
-
Tolerance for
lambda = 0
; defaults to 0.02.
- xlab
-
defaults to
"lambda"
.
- ylab
-
defaults to
"log-Likelihood"
.
- ...
-
additional parameters to be used in the model fitting.
VALUE:
A list of the
lambda
vector and the
computed profile log-likelihood vector, invisibly if the result is
plotted.
SIDE EFFECTS:
If
plotit = T
plots loglik vs
lambda
and indicates a 95% confidence
interval about the maximum observed value of
lambda
. If
interp = T
, spline interpolation is used
to give a smoother plot.
EXAMPLES:
boxcox(volume ~ log(height) + log(diam), data = trees,
lambda = seq(-0.25, 0.25, length = 10))
boxcox(Days+1 ~ Eth*Sex*Age*Lrn, data = quine, singular.ok = T,
lambda = seq(-0.05, 0.45, len = 20))