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<html><head><title>R: Log Multivariate Normal Density</title>
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<table width="100%" summary="page for ldmvnorm {sbgcop}"><tr><td>ldmvnorm {sbgcop}</td><td align="right">R Documentation</td></tr></table>
<h2>Log Multivariate Normal Density</h2>
<h3>Description</h3>
<p>
Computes the log of the multivariate normal density
</p>
<h3>Usage</h3>
<pre>
ldmvnorm(Y, S)
</pre>
<h3>Arguments</h3>
<table summary="R argblock">
<tr valign="top"><td><code>Y</code></td>
<td>
an n x p matrix </td></tr>
<tr valign="top"><td><code>S</code></td>
<td>
a p x p positive definite matrix </td></tr>
</table>
<h3>Details</h3>
<p>
This function computes the log density of the data matrix <code>Y</code>
under the model that the rows are independent samples from a
mean-zero multivariate normal distribution with covariance matrix
<code>S</code>.
</p>
<h3>Value</h3>
<p>
A real number.</p>
<h3>Author(s)</h3>
<p>
Peter Hoff
</p>
<h3>Examples</h3>
<pre>
Y<-matrix(rnorm(9*7),9,7)
ldmvnorm(Y,diag(7))
</pre>
<hr><div align="center">[Package <em>sbgcop</em> version 0.95 <a href="00Index.html">Index]</a></div>
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