class_docstr: Inherits time series methods from TSM class.
  
  **** NON-GAUSSIAN LOCAL LINEAR TREND MODEL ****
  
  Parameters
  ----------
  data : pd.DataFrame or np.array
      Field to specify the time series data that will be used.
  
  integ : int (default : 0)
      Specifies how many time to difference the time series.
  
  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.
  
  family : 
      e.g. pf.Normal(0,1)
class_docstr_tok: ["Inherits","time","series","methods","from","TSM","class",".","*","*","*","*","NON-GAUSSIAN","LOCAL","LINEAR","TREND","MODEL","*","*","*","*","Parameters","--","--","--","--","--","data",":","pd.DataFrame","or","np.array","Field","to","specify","the","time","series","data","that","will","be","used",".","integ",":","int","(","default",":","0",")","Specifies","how","many","time","to","difference","the","time","series",".","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",".","family",":","e.g",".","pf.Normal","(","0,1",")"]
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(
          "Sigma^2 level", fam.Flat(transform="exp"), fam.Normal(0, 3)
      )
      self.latent_variables.add_z(
          "Sigma^2 trend", fam.Flat(transform="exp"), fam.Normal(0, 3)
      )
  
imports: import sys
  import numpy
  import pandas
  import scipy.stats
  from scipy import optimize
  from ..None import inference
  from ..None import families
  from ..None import output
  from ..None import tsm
  from ..None import data_check
  from ..None import covariances
  from ..None import results
  from ..None import gas
  from .kalman import *
  from .llt import *
label_desc: Use image node_id 12 for calling the NLLT obj's underlying member method code with example usage: obj._create_latent_variables() without return types