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+<html>
+<head>
+<title>
+Netlab Reference Manual gpcovarp
+</title>
+</head>
+<body>
+<H1> gpcovarp
+</H1>
+<h2>
+Purpose
+</h2>
+Calculate the prior covariance for a Gaussian Process.
+
+<p><h2>
+Synopsis
+</h2>
+<PRE>
+covp = gpcovarp(net, x1, x2)
+[covp, covf] = gpcovarp(net, x1, x2)
+</PRE>
+
+
+<p><h2>
+Description
+</h2>
+
+<p><CODE>covp = gpcovarp(net, x1, x2)</CODE> takes 
+a Gaussian Process data structure <CODE>net</CODE> together with
+two matrices <CODE>x1</CODE> and <CODE>x2</CODE> of input vectors, 
+and computes the matrix of the prior covariance.  This is
+the function component of the covariance plus the exponential of the bias
+term.  
+
+<p><CODE>[covp, covf] = gpcovarp(net, x1, x2)</CODE> also returns the function
+component of the covariance.
+
+<p><h2>
+See Also
+</h2>
+<CODE><a href="gp.htm">gp</a></CODE>, <CODE><a href="gpcovar.htm">gpcovar</a></CODE>, <CODE><a href="gpcovarf.htm">gpcovarf</a></CODE>, <CODE><a href="gperr.htm">gperr</a></CODE>, <CODE><a href="gpgrad.htm">gpgrad</a></CODE><hr>
+<b>Pages:</b>
+<a href="index.htm">Index</a>
+<hr>
+<p>Copyright (c) Ian T Nabney (1996-9)
+
+
+</body>
+</html>
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