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<table width="100%" summary="page for profile.glm {MASS}"><tr><td>profile.glm {MASS}</td><td align="right">R Documentation</td></tr></table>
<h2>Method for Profiling glm Objects</h2>
<h3>Description</h3>
<p>
Investigates the profile log-likelihood function for a fitted model of
class <code>"glm"</code>.
</p>
<h3>Usage</h3>
<pre>
## S3 method for class 'glm':
profile(fitted, which = 1:p, alpha = 0.01, maxsteps = 10,
del = zmax/5, trace = FALSE, ...)
</pre>
<h3>Arguments</h3>
<table summary="R argblock">
<tr valign="top"><td><code>fitted</code></td>
<td>
the original fitted model object.</td></tr>
<tr valign="top"><td><code>which</code></td>
<td>
the original model parameters which should be profiled.
This can be a numeric or character vector.
By default, all parameters are profiled.</td></tr>
<tr valign="top"><td><code>alpha</code></td>
<td>
highest significance level allowed for the
profile t-statistics.</td></tr>
<tr valign="top"><td><code>maxsteps</code></td>
<td>
maximum number of points to be used for profiling each
parameter.</td></tr>
<tr valign="top"><td><code>del</code></td>
<td>
suggested change on the scale of the profile
t-statistics. Default value chosen to allow profiling at about
10 parameter values.</td></tr>
<tr valign="top"><td><code>trace</code></td>
<td>
logical: should the progress of profiling be reported?</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
further arguments passed to or from other methods.</td></tr>
</table>
<h3>Details</h3>
<p>
The profile t-statistic is defined as the square root of change in
sum-of-squares divided by residual standard error with an
appropriate sign.
</p>
<h3>Value</h3>
<p>
A list of classes <code>"profile.glm"</code> and <code>"profile"</code> with an
element for each parameter being profiled. The elements are
data-frames with two variables
</p>
<table summary="R argblock">
<tr valign="top"><td><code>par.vals</code></td>
<td>
a matrix of parameter values for each fitted model.</td></tr>
<tr valign="top"><td><code>tau</code></td>
<td>
the profile t-statistics.</td></tr>
</table>
<h3>Author(s)</h3>
<p>
Originally, D. M. Bates and W. N. Venables. (For S in 1996.)
</p>
<h3>See Also</h3>
<p>
<code><a href="../../VGAM/html/notdocumentedyet.html">glm</a></code>, <code><a href="../../stats/html/profile.html">profile</a></code>, <code><a href="plot.profile.html">plot.profile</a></code>
</p>
<h3>Examples</h3>
<pre>
options(contrasts = c("contr.treatment", "contr.poly"))
ldose <- rep(0:5, 2)
numdead <- c(1, 4, 9, 13, 18, 20, 0, 2, 6, 10, 12, 16)
sex <- factor(rep(c("M", "F"), c(6, 6)))
SF <- cbind(numdead, numalive = 20 - numdead)
budworm.lg <- glm(SF ~ sex*ldose, family = binomial)
pr1 <- profile(budworm.lg)
plot(pr1)
pairs(pr1)
</pre>
<hr><div align="center">[Package <em>MASS</em> version 7.2-44 <a href="00Index.html">Index]</a></div>
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