code: def plot_fit(self,**kwargs):
          
          import matplotlib.pyplot as plt
          import seaborn as sns
  
          figsize = kwargs.get('figsize',(10,7))
  
          if self.latent_variables.estimated is False:
              raise Exception("No latent variables estimated!")
          else:
              date_index = self.index[self.lags:self.data[0].shape[0]]
              mu, Y = self._model(self.latent_variables.get_z_values())
              for series in range(0,Y.shape[0]):
                  plt.figure(figsize=figsize)
                  plt.plot(date_index,Y[series],label='Data ' + str(series))
                  plt.plot(date_index,mu[series],label='Filter' + str(series),c='black')  
                  plt.title(self.data_name[series])
                  plt.legend(loc=2)   
              plt.show()
docs: Plots the fit of the model
  
          Returns
          ----------
          None (plots data and the fit)