class_docstr: Inherits time series methods from TSM class.
  
  **** BETA-t-EGARCH IN MEAN REGRESSION MODELS ****
  
  Parameters
  ----------
  data : pd.DataFrame
      Field to specify the time series data that will be used.
  
  p : int
      Field to specify how many GARCH terms the model will have.
  
  q : int
      Field to specify how many SCORE terms the model will have.
  
  formula : string
      patsy string describing the regression
class_docstr_tok: ["Inherits","time","series","methods","from","TSM","class",".","*","*","*","*","BETA-t-EGARCH","IN","MEAN","REGRESSION","MODELS","*","*","*","*","Parameters","--","--","--","--","--","data",":","pd.DataFrame","Field","to","specify","the","time","series","data","that","will","be","used",".","p",":","int","Field","to","specify","how","many","GARCH","terms","the","model","will","have",".","q",":","int","Field","to","specify","how","many","SCORE","terms","the","model","will","have",".","formula",":","string","patsy","string","describing","the","regression"]
docstr: Plots the fit of the model
  
  Returns
  ----------
  None (plots data and the fit)
docstr_tok: ["Plots","the","fit","of","the","model","Returns","--","--","--","--","--","None","(","plots","data","and","the","fit",")"]
code: def plot_fit(self, **kwargs):
      """Plots the fit of the model
  
      Returns
      ----------
      None (plots data and the fit)
      """
      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:
          t_params = self.transform_z()
          plt.figure(figsize=figsize)
          date_index = self.index[max(self.p, self.q) :]
          sigma2, Y, ___, theta = self._model(
              self.latent_variables.get_z_values()
          )
          plt.plot(
              date_index,
              np.abs(Y - theta),
              label=self.data_name + " Absolute Demeaned Values",
          )
          plt.plot(
              date_index,
              np.exp(sigma2 / 2.0),
              label="EGARCHMREG("
              + str(self.p)
              + ","
              + str(self.q)
              + ") Conditional Volatility",
              c="black",
          )
          plt.title(self.data_name + " Volatility Plot")
          plt.legend(loc=2)
          plt.show()
  
imports: import sys
  import numpy
  import pandas
  import scipy.stats
  from patsy import dmatrices, dmatrix, demo_data
  from ..None import families
  from ..None import output
  from ..None import tests
  from ..None import tsm
  from ..None import gas
  from ..None import data_check
label_desc: Use image node_id 13 for calling the EGARCHMReg obj's underlying member method code with example usage: obj.plot_fit() without return types