e <tt>sn</tt> is set to
0.1. Again, the representation in the <tt>hyp.lik</tt> is given in
terms of its logarithm. For more information about likelihood
functions, see <a href="../likFunctions.m">likFunctions</a> and <a
 href="../lik">lik/</a>.</p>

<p>Then, we generate a dataset with <tt>n=20</tt> examples. The inputs
<tt>x</tt> are drawn from a unit Gaussian (using the
<tt>gpml_randn</tt> utility, which generates unit Gaussian pseudo
random numbers with a specified seed). We then evaluate the covariance
m