">gp</a>, it does posterior inference, learns
hyperparameters, computes the marginal likelihood and makes
predictions. Generally, the gp function takes the following arguments:
a hyperparameter struct, an inference method, a mean function, a
covariance function, a likelihood function, training inputs, training
targets, and possibly test cases. The exact computations done by the
function is controlled by the number of input and output arguments in
the call. Here is part of the help message for the <a
href=".