def pdf_link(self, link_f, y, Y_metadata=None):
assert np.atleast_1d(link_f).shape == np.atleast_1d(y).shape<EOL>log_objective = link_f*np.exp(-y*link_f)<EOL>return np.exp(np.sum(np.log(log_objective)))<EOL>
Likelihood function given link(f)

.. math::
    p(y_{i}|\\lambda(f_{i})) = \\lambda(f_{i})\\exp (-y\\lambda(f_{i}))

:param link_f: latent variables link(f)
:type link_f: Nx1 array
:param y: data
:type y: Nx1 array
:param Y_metadata: Y_metadata which is not used in exponential distribution
:returns: likelihood evaluated for this point
:rtype: float