boxcox
Box-Cox Transformations for Linear Models
Computes and optionally plots profile log-likelihoods for the parameter of the Box-Cox power transformation.
- Keywords
- models, hplot, regression
Usage
boxcox(object, …)# S3 method for default
boxcox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp, eps = 1/50, xlab = expression(lambda),
ylab = "log-Likelihood", …)
# S3 method for formula
boxcox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp, eps = 1/50, xlab = expression(lambda),
ylab = "log-Likelihood", …)
# S3 method for lm
boxcox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
interp, eps = 1/50, xlab = expression(lambda),
ylab = "log-Likelihood", …)
Arguments
- object
a formula or fitted model object. Currently only
lmandaovobjects 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.
- interp
logical which controls whether spline interpolation is used. Default to
TRUEif plotting withlambdaof 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 = TRUE plots log-likelihood vs lambda and
indicates a 95% confidence interval about the maximum observed value
of lambda. If interp = TRUE, spline interpolation is
used to give a smoother plot.
References
Box, G. E. P. and Cox, D. R. (1964) An analysis of transformations (with discussion). Journal of the Royal Statistical Society B, 26, 211--252.
Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.
Examples
# NOT RUN {
boxcox(Volume ~ log(Height) + log(Girth), data = trees,
lambda = seq(-0.25, 0.25, length = 10))
boxcox(Days+1 ~ Eth*Sex*Age*Lrn, data = quine,
lambda = seq(-0.05, 0.45, len = 20))
# }