boxcox: 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, ...)
# 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", ...)

Value

A list of the lambda vector and the computed profile log-likelihood vector, invisibly if the result is plotted.

Arguments

object: 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.
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.

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

Run this code

boxcox(Volume ~ log(Height) + log(Girth), data = trees,
       lambda = seq(-0.25, 0.25, length.out = 10))

boxcox(Days+1 ~ Eth*Sex*Age*Lrn, data = quine,
       lambda = seq(-0.05, 0.45, length.out = 20))

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