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: Creates model latent variables
  
  Returns
  ----------
  None (changes model attributes)
docstr_tok: ["Creates","model","latent","variables","Returns","--","--","--","--","--","None","(","changes","model","attributes",")"]
code: def _create_latent_variables(self):
      """Creates model latent variables
  
      Returns
      ----------
      None (changes model attributes)
      """
  
      self.latent_variables.add_z(
          "Vol Constant",
          fam.Normal(0, 3, transform="exp"),
          fam.Normal(0, 3),
      )
      self.latent_variables.z_list[0].start = -7.00
  
      for q_term in range(self.q):
          self.latent_variables.add_z(
              "q(" + str(q_term + 1) + ")",
              fam.Normal(0, 0.5, transform="logit"),
              fam.Normal(0, 3),
          )
          if q_term == 0:
              self.latent_variables.z_list[-1].start = -1.50
          else:
              self.latent_variables.z_list[-1].start = -4.00
  
      for p_term in range(self.p):
          self.latent_variables.add_z(
              "p(" + str(p_term + 1) + ")",
              fam.Normal(0, 0.5, transform="logit"),
              fam.Normal(0, 3),
          )
          if p_term == 0:
              self.latent_variables.z_list[-1].start = 3.00
          else:
              self.latent_variables.z_list[-1].start = -4.00
  
      self.latent_variables.add_z(
          "Returns Constant",
          fam.Normal(0, 3, transform=None),
          fam.Normal(0, 3),
      )
  
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 2 for calling the GARCH obj's underlying member method code with example usage: obj._create_latent_variables() without return types