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<table width="100%" summary="page for predict.trls {spatial}"><tr><td>predict.trls {spatial}</td><td align="right">R Documentation</td></tr></table>
<h2>Predict method for trend surface fits</h2>


<h3>Description</h3>

<p>
Predicted values based on trend surface model object
</p>


<h3>Usage</h3>

<pre>
## S3 method for class 'trls':
predict(object, x, y, ...)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>object</code></td>
<td>
Fitted trend surface model object returned by <code>surf.ls</code>
</td></tr>
<tr valign="top"><td><code>x</code></td>
<td>
Vector of prediction location eastings (x coordinates)
</td></tr>
<tr valign="top"><td><code>y</code></td>
<td>
Vector of prediction location northings (y coordinates)
</td></tr>
<tr valign="top"><td><code>...</code></td>
<td>
further arguments passed to or from other methods.
</td></tr>
</table>

<h3>Value</h3>

<p>
<code>predict.trls</code> produces a vector of predictions corresponding
to the prediction locations. To display the output with <code>image</code>
or <code>contour</code>, use <code>trmat</code> or convert the returned vector
to matrix form.</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="surf.ls.html">surf.ls</a></code>, <code><a href="trmat.html">trmat</a></code>
</p>


<h3>Examples</h3>

<pre>
data(topo, package="MASS")
topo2 &lt;- surf.ls(2, topo)
topo4 &lt;- surf.ls(4, topo)
x &lt;- c(1.78, 2.21)
y &lt;- c(6.15, 6.15)
z2 &lt;- predict(topo2, x, y)
z4 &lt;- predict(topo4, x, y)
cat("2nd order predictions:", z2, "\n4th order predictions:", z4, "\n")
</pre>



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

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