r"""
        Binomial log likelihood.

        Parameters
        ----------
        y: ndarray
            array of 0, 1 valued integers of targets
        f: ndarray
            latent function from the GLM prior (:math:`\mathbf{f} =
            \boldsymbol\Phi \mathbf{w}`)
        n: ndarray
            the total number of observations

        Returns
        -------
        logp: ndarray
            the log likelihood of each y given each f under this
            likelihood.

def loglike(self, y, f, n):
        r"""
        Binomial log likelihood.

        Parameters
        ----------
        y: ndarray
            array of 0, 1 valued integers of targets
        f: ndarray
            latent function from the GLM prior (:math:`\mathbf{f} =
            \boldsymbol\Phi \mathbf{w}`)
        n: ndarray
            the total number of observations

        Returns
        -------
        logp: ndarray
            the log likelihood of each y given each f under this
            likelihood.
        """
        ll = binom.logpmf(y, n=n, p=expit(f))
        return ll