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<html><head><title>R: Estimate log Transformation Parameter</title>
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<table width="100%" summary="page for logtrans {MASS}"><tr><td>logtrans {MASS}</td><td align="right">R Documentation</td></tr></table>
<h2>Estimate log Transformation Parameter</h2>


<h3>Description</h3>

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


<h3>Usage</h3>

<pre>
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, ...)

## S3 method for class 'lm':
logtrans(object, ...)
</pre>


<h3>Arguments</h3>

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

<h3>Value</h3>

<p>
List with components <code>x</code> (for alpha) and <code>y</code> (for the marginal
log-likelihood values).</p>

<h3>Side Effects</h3>

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


<h3>References</h3>

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


<h3>See Also</h3>

<p>
<code><a href="boxcox.html">boxcox</a></code>
</p>


<h3>Examples</h3>

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



<hr><div align="center">[Package <em>MASS</em> version 7.2-44 <a href="00Index.html">Index]</a></div>

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