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date | Tue, 10 Feb 2015 15:05:51 +0000 |
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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>