nlZ dnlZ          ] = gp(hyp, inf, mean, cov, lik, x, y);
  prediction: [ymu ys2 fmu fs2   ] = gp(hyp, inf, mean, cov, lik, x, y, xs);
          or: [ymu ys2 fmu fs2 lp] = gp(hyp, inf, mean, cov, lik, x, y, xs, ys);

  [ .. snip ...]
</pre>

<p>Here <tt>x</tt> and <tt>y</tt> are training inputs and outputs, and
<tt>xs</tt> and <tt>ys</tt> are test set inputs and outputs,  
<tt>nlZ</tt> is the negative log marginal likelihood and
<tt>dnlZ</tt> its partial derivatives wrt the hyperparameters (which
are used f