Last data update: 2014.03.03

R: Box-Cox Transformations for Linear Models
boxcoxR 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 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

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))

Results


R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(MASS)
> png(filename="/home/ddbj/snapshot/RGM3/R_CC/result/MASS/boxcox.Rd_%03d_medium.png", width=480, height=480)
> ### Name: boxcox
> ### Title: Box-Cox Transformations for Linear Models
> ### Aliases: boxcox boxcox.default boxcox.formula boxcox.lm
> ### Keywords: regression models hplot
> 
> ### ** Examples
> 
> 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))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>