class_docstr: Inherits time series methods from TSM class.
  
  **** GENERALIZED AUTOREGRESSIVE CONDITIONAL HETEROSCEDASTICITY (GARCH) MODELS ****
  
  Parameters
  ----------
  data : pd.DataFrame or np.array
      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 ARCH terms the model will have.
  
  target : str (pd.DataFrame) or int (np.array)
      Specifies which column name or array index to use. By default, first
      column/array will be selected as the dependent variable.
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:
          plt.figure(figsize=figsize)
          date_index = self.index[max(self.p, self.q) :]
          t_params = self.transform_z()
          sigma2, Y, ___ = self._model(
              self.latent_variables.get_z_values()
          )
          plt.plot(
              date_index,
              np.abs(Y - t_params[-1]),
              label=self.data_name + " Absolute Demeaned Values",
          )
          plt.plot(
              date_index,
              np.power(sigma2, 0.5),
              label="GARCH("
              + 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 ..None import families
  from ..None import output
  from ..None import tests
  from ..None import tsm
  from ..None import data_check
  from .garch_recursions import garch_recursion
label_desc: Use image node_id 12 for calling the GARCH obj's underlying member method code with example usage: obj.plot_fit() without return types