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: Obtains appropriate model scale and shape latent variables
  
  Parameters
  ----------
  parm : np.array
      Transformed latent variables vector
  
  Returns
  ----------
  None (changes model attributes)
docstr_tok: ["Obtains","appropriate","model","scale","and","shape","latent","variables","Parameters","--","--","--","--","--","parm",":","np.array","Transformed","latent","variables","vector","Returns","--","--","--","--","--","None","(","changes","model","attributes",")"]
code: def _get_scale_and_shape(self, parm):
      """Obtains appropriate model scale and shape latent variables
  
      Parameters
      ----------
      parm : np.array
          Transformed latent variables vector
  
      Returns
      ----------
      None (changes model attributes)
      """
  
      if self.scale is True:
          if self.shape is True:
              model_shape = parm[-1]
              model_scale = parm[-2]
          else:
              model_shape = 0
              model_scale = parm[-1]
      else:
          model_scale = 0
          model_shape = 0
  
      if self.skewness is True:
          model_skewness = parm[-3]
      else:
          model_skewness = 0
  
      return model_scale, model_shape, model_skewness
  
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 2 for calling the NLLT obj's underlying member method code with example usage: obj._get_scale_and_shape(parm) and returns: model_scale,  model_shape,  model_skewness