# logtrans

From MASS v7.3-16
by Brian Ripley

##### Estimate log Transformation Parameter

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

.

- Keywords
- models, hplot, regression

##### Usage

`logtrans(object, ...)`## S3 method for class 'default':
logtrans(object, \dots, 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, \dots)

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

##### 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
- optional
`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

##### Examples

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

*Documentation reproduced from package MASS, version 7.3-16, License: GPL-2 | GPL-3*

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