boxcox {MASS} | R Documentation

## Box-Cox Transformations for Linear Models

### Description

Computes and optionally plots profile log-likelihoods for the parameter of the Box-Cox simple power transformation `y^lambda`.

### Usage

    boxcox(object, lambda, plotit, interp, eps, xlab, ylab, ...)

### 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. 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.

### 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.

### Examples

    data(trees)
    boxcox(Volume ~ log(Height) + log(Girth), data = trees,
           lambda = seq(-0.25, 0.25, length = 10))
    data(quine)
    boxcox(Days+1 ~ Eth*Sex*Age*Lrn, data = quine, singular.ok = TRUE,
     lambda = seq(-0.05, 0.45, len = 20))