Box-Cox Transformations for Linear Models
Usage
boxcox(model, lambda, plotit, interp, eps, xlab, ylab, ...)
Arguments
model
|
a formula or fitted model object. Currently only lm and aov objects
are handled.
|
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 to true 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.
|
Description
Computes and optionally plots profile log-likelihoods for the
parameter of the Box-Cox simple power transformation y^lambda
.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
data(trees)
boxcox(volume ~ log(height) + log(diam), data = trees,
lambda = seq(-0.25, 0.25, length = 10))