def sample(self, nsims=1000):
        """ Samples from the posterior predictive distribution

        Parameters
        ----------
        nsims : int (default : 1000)
            How many draws from the posterior predictive distribution

        Returns
        ----------
        - np.ndarray of draws from the data
        """     
        if self.latent_variables.estimation_method not in ['BBVI', 'M-H']:
            raise Exception("No latent variables estimated!")
        else:
            lv_draws = self.draw_latent_variables(nsims=nsims)
            mus = [self._model(lv_draws[:,i])[0] for i in range(nsims)]
            model_scale, model_shape, model_skewness = self._get_scale_and_shape_sim(lv_draws)
            data_draws = np.array([self.family.draw_variable(self.link(mus[i]), 
                np.repeat(model_scale[i], mus[i].shape[0]), np.repeat(model_shape[i], mus[i].shape[0]), 
                np.repeat(model_skewness[i], mus[i].shape[0]), mus[i].shape[0]) for i in range(nsims)])
            return data_draws
def sample ( self , nsims = 1000 ) : if self . latent_variables . estimation_method not in [ 'BBVI' , 'M-H' ] : raise Exception ( "No latent variables estimated!" ) else : lv_draws = self . draw_latent_variables ( nsims = nsims ) mus = [ self . _model ( lv_draws [ : , i ] ) [ 0 ] for i in range ( nsims ) ] model_scale , model_shape , model_skewness = self . _get_scale_and_shape_sim ( lv_draws ) data_draws = np . array ( [ self . family . draw_variable ( self . link ( mus [ i ] ) , np . repeat ( model_scale [ i ] , mus [ i ] . shape [ 0 ] ) , np . repeat ( model_shape [ i ] , mus [ i ] . shape [ 0 ] ) , np . repeat ( model_skewness [ i ] , mus [ i ] . shape [ 0 ] ) , mus [ i ] . shape [ 0 ] ) for i in range ( nsims ) ] ) return data_draws
Samples from the posterior predictive distribution

        Parameters
        ----------
        nsims : int (default : 1000)
            How many draws from the posterior predictive distribution

        Returns
        ----------
        - np.ndarray of draws from the data