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<table width="100%" summary="page for GP.std.grids"><tr><td>GP.std.grids</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Compute the standardized grids</h2>

<h3>Description</h3>

<p>Compute the standardized grids
</p>


<h3>Usage</h3>

<pre>
GP.std.grids(
  grids,
  center = apply(grids, 2, mean),
  scale = NULL,
  max_range = 6
)
</pre>


<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>grids</code></td>
<td>
<p>A matrix where rows represent grid points and columns are coordinates.</p>
</td></tr>
<tr valign="top"><td><code>center</code></td>
<td>
<p>A vector of real numbers specifying the centroid parameters in the modified exponential squared kernel. The default value is NULL and set to the center of the grid points: apply(x,2,mean).</p>
</td></tr>
<tr valign="top"><td><code>scale</code></td>
<td>
<p>A vector of positive numbers specifying the scale parameters in the modified exponential squared kernel. The default value is NULL and set to values such that grid points in a range of (-max_range,max_range) in each dimension.</p>
</td></tr>
<tr valign="top"><td><code>max_range</code></td>
<td>
<p>A positive real number indicating the maximum range of the grid points to specify the scale parameter. The default value is NULL and set to 6.</p>
</td></tr>
</table>


<h3>Value</h3>

<p>A matrix where rows represent the standardized grids.
</p>


<h3>Author(s)</h3>

<p>Jian Kang &lt;jiankang@umich.edu&gt;
</p>


<h3>Examples</h3>

<pre>
library(BayesGPfit)
grids = GP.generate.grids(d=2L)
std_grids = GP.std.grids(grids)
plot(grids[,1],std_grids[,1],asp=1,type="l")
abline(a=0,b=1,lty=2)
</pre>


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