logtrans {MASS} | R Documentation

## Estimate log Transformation Parameter

### Description

Find and optionally plot the marginal likelihood for alpha for a transformation model of the form `log(y + alpha) ~ x1 + x2 + ...`.

### Usage

    logtrans(object, ...)

    ## Default S3 method:
    logtrans(object, ..., alpha = seq(0.5, 6, by = 0.25) - min(y),
             plotit = TRUE, interp =, xlab = "alpha", ylab = "log Likelihood")

    ## S3 method for class 'formula':
    logtrans(object, data = NULL, ...)

    ## S3 method for class 'lm':
    logtrans(object, ...)

### Arguments

`object` | Fitted linear model object, or formula defining the untransformed model that is `y ~ x1 + x2 + ...`. The function is generic.
`...` | If `object` is a formula, this argument may specify a data frame as for `lm`.
`alpha` | Set of values for the transformation parameter, alpha.
`plotit` | Should plotting be done?
`interp` | Should the marginal log-likelihood be interpolated with a spline approximation? (Default is `TRUE` if plotting is to be done and the number of real points is less than 100.)
`xlab` | as for `plot`.
`ylab` | as for `plot`.
`data` | `data` argument for `lm` fit.

### Value

List with components `x` (for alpha) and `y` (for the marginal log-likelihood values).

### Side Effects

A plot of the marginal log-likelihood is produced, if requested, together with an approximate mle and 95% confidence interval.

### References

Venables, W. N. and Ripley, B. D. (2002) Modern Applied Statistics with S. Fourth edition. Springer.

### See Also

`boxcox`

### Examples

    logtrans(Days ~ Age*Sex*Eth*Lrn, data = quine,
             alpha = seq(0.75, 6.5, len=20))

[Package Contents]