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 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))

[Package

*MASS* version 7.2-23

Index]