boxcox                 package:MASS                 R Documentation

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, ...)

     ## Default S3 method:
     boxcox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
            interp, eps = 1/50, xlab = expression(lambda),
            ylab = "log-Likelihood", ...)

     ## S3 method for class 'formula':
     boxcox(object, lambda = seq(-2, 2, 1/10), plotit = TRUE,
            interp, eps = 1/50, xlab = expression(lambda),
            ylab = "log-Likelihood", ...)

     ## S3 method for class '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 '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.

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 loglik _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:

     data(trees)
     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))

