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| author | Daniel Wolff |
|---|---|
| date | Fri, 19 Aug 2016 13:07:06 +0200 |
| parents | |
| children |
| rev | line source |
|---|---|
| Daniel@0 | 1 <html> |
| Daniel@0 | 2 <head> |
| Daniel@0 | 3 <title> |
| Daniel@0 | 4 Netlab Reference Manual gpcovarf |
| Daniel@0 | 5 </title> |
| Daniel@0 | 6 </head> |
| Daniel@0 | 7 <body> |
| Daniel@0 | 8 <H1> gpcovarf |
| Daniel@0 | 9 </H1> |
| Daniel@0 | 10 <h2> |
| Daniel@0 | 11 Purpose |
| Daniel@0 | 12 </h2> |
| Daniel@0 | 13 Calculate the covariance function for a Gaussian Process. |
| Daniel@0 | 14 |
| Daniel@0 | 15 <p><h2> |
| Daniel@0 | 16 Synopsis |
| Daniel@0 | 17 </h2> |
| Daniel@0 | 18 <PRE> |
| Daniel@0 | 19 covf = gpcovarf(net, x1, x2) |
| Daniel@0 | 20 </PRE> |
| Daniel@0 | 21 |
| Daniel@0 | 22 |
| Daniel@0 | 23 <p><h2> |
| Daniel@0 | 24 Description |
| Daniel@0 | 25 </h2> |
| Daniel@0 | 26 |
| Daniel@0 | 27 <p><CODE>covf = gpcovarf(net, x1, x2)</CODE> takes |
| Daniel@0 | 28 a Gaussian Process data structure <CODE>net</CODE> together with |
| Daniel@0 | 29 two matrices <CODE>x1</CODE> and <CODE>x2</CODE> of input vectors, |
| Daniel@0 | 30 and computes the matrix of the covariance function values |
| Daniel@0 | 31 <CODE>covf</CODE>. |
| Daniel@0 | 32 |
| Daniel@0 | 33 <p><h2> |
| Daniel@0 | 34 See Also |
| Daniel@0 | 35 </h2> |
| Daniel@0 | 36 <CODE><a href="gp.htm">gp</a></CODE>, <CODE><a href="gpcovar.htm">gpcovar</a></CODE>, <CODE><a href="gpcovarp.htm">gpcovarp</a></CODE>, <CODE><a href="gperr.htm">gperr</a></CODE>, <CODE><a href="gpgrad.htm">gpgrad</a></CODE><hr> |
| Daniel@0 | 37 <b>Pages:</b> |
| Daniel@0 | 38 <a href="index.htm">Index</a> |
| Daniel@0 | 39 <hr> |
| Daniel@0 | 40 <p>Copyright (c) Ian T Nabney (1996-9) |
| Daniel@0 | 41 |
| Daniel@0 | 42 |
| Daniel@0 | 43 </body> |
| Daniel@0 | 44 </html> |