code: def plot_sample(self, nsims=10, plot_data=True, **kwargs):
          
  
          if self.latent_variables.estimation_method not in ['BBVI', 'M-H']:
              raise Exception("No latent variables estimated!")
          else:
              import matplotlib.pyplot as plt
              import seaborn as sns
  
              figsize = kwargs.get('figsize',(10,7))
              plt.figure(figsize=figsize)
              date_index = self.index[max(self.ar, self.sc):self.data_length]
              mu, Y, scores = self._model(self.latent_variables.get_z_values())
              draws = self.sample(nsims).T
              plt.plot(date_index, draws, label='Posterior Draws', alpha=1.0)
              if plot_data is True:
                  plt.plot(date_index, Y, label='Data', c='black', alpha=0.5, linestyle='', marker='s')
              plt.title(self.data_name)
              plt.show()
docs: Plots draws from the posterior predictive density against the data
  
          Parameters
          ----------
          nsims : int (default : 1000)
              How many draws from the posterior predictive distribution
  
          plot_data boolean
              Whether to plot the data or not