predict.lqs.html

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<html><head><title>R: Predict from an lqs Fit</title>
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<table width="100%" summary="page for predict.lqs {MASS}"><tr><td>predict.lqs {MASS}</td><td align="right">R Documentation</td></tr></table>
<h2>Predict from an lqs Fit</h2>


<h3>Description</h3>

<p>
Predict from an resistant regression fitted by <code>lqs</code>.
</p>


<h3>Usage</h3>

<pre>
## S3 method for class 'lqs':
predict(object, newdata, na.action = na.pass, ...)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>object</code></td>
<td>
object inheriting from class <code>"lqs"</code>
</td></tr>
<tr valign="top"><td><code>newdata</code></td>
<td>
matrix or data frame of cases to be predicted or, if <code>object</code>
has a formula, a data frame with columns of the same names as the
variables used.  A vector will be interpreted
as a row vector.  If <code>newdata</code> is missing, an attempt will be
made to retrieve the data used to fit the <code>lqs</code> object.
</td></tr>
<tr valign="top"><td><code>na.action</code></td>
<td>
function determining what should be done with missing
values in <code>newdata</code>.  The default is to predict <code>NA</code>.</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
arguments to be passed from or to other methods.</td></tr>
</table>

<h3>Details</h3>

<p>
This function is a method for the generic function
<code>predict()</code> for class <code>lqs</code>.
It can be invoked by calling <code>predict(x)</code> for an
object <code>x</code> of the appropriate class, or directly by
calling <code>predict.lqs(x)</code> regardless of the
class of the object.
</p>
<p>
Missing values in <code>newdata</code> are handled by returning <code>NA</code> if the
linear fit cannot be evaluated. If <code>newdata</code> is omitted and
the <code>na.action</code> of the fit omitted cases, these will be omitted on the
prediction.
</p>


<h3>Value</h3>

<p>
A vector of predictions.</p>

<h3>Author(s)</h3>

<p>
B.D. Ripley
</p>


<h3>See Also</h3>

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


<h3>Examples</h3>

<pre>
set.seed(123)
fm &lt;- lqs(stack.loss ~ ., data = stackloss, method = "S", nsamp = "exact")
predict(fm, stackloss)
</pre>



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

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