 hyp.cov, x);
  mu = feval(meanfunc{:}, hyp.mean, x);
  y = chol(K)'*gpml_randn(0.15, n, 1) + mu + exp(hyp.lik)*gpml_randn(0.2, n, 1);

  plot(x, y, '+')
</pre>

<p>Above, we first specify the mean function <tt>meanfunc</tt>,
covariance function <tt>covfunc</tt> of a GP and a likelihood
function, <tt>likfunc</tt>. The corresponding hyperparameters are
specified in the <tt>hyp</tt> structure:</p>

<p>The <b>mean function</b> is composite, adding (using <tt>meanSum</tt>
function) a linear (<tt>meanLinear</tt>