def mb_neg_logposterior(self, beta, mini_batch):
        """ Returns negative log posterior

        Parameters
        ----------
        beta : np.array
            Contains untransformed starting values for latent variables

        mini_batch : int
            Batch size for the data

        Returns
        ----------
        Negative log posterior
        """

        post = (self.data.shape[0]/mini_batch)*self.mb_neg_loglik(beta, mini_batch)
        for k in range(0,self.z_no):
            post += -self.latent_variables.z_list[k].prior.logpdf(beta[k])
        return post
def mb_neg_logposterior ( self , beta , mini_batch ) : post = ( self . data . shape [ 0 ] / mini_batch ) * self . mb_neg_loglik ( beta , mini_batch ) for k in range ( 0 , self . z_no ) : post += - self . latent_variables . z_list [ k ] . prior . logpdf ( beta [ k ] ) return post
Returns negative log posterior

        Parameters
        ----------
        beta : np.array
            Contains untransformed starting values for latent variables

        mini_batch : int
            Batch size for the data

        Returns
        ----------
        Negative log posterior