class_docstr: Inherits time series methods from TSM class.
  
  **** DYNAMIC AUTOREGRESSIVE MODEL ****
  
  Parameters
  ----------
  
  ar : int
      Number of autoregressive lags
  
  data : pd.DataFrame
      Field to specify the data that will be used
class_docstr_tok: ["Inherits","time","series","methods","from","TSM","class",".","*","*","*","*","DYNAMIC","AUTOREGRESSIVE","MODEL","*","*","*","*","Parameters","--","--","--","--","--","ar",":","int","Number","of","autoregressive","lags","data",":","pd.DataFrame","Field","to","specify","the","data","that","will","be","used"]
docstr: Creates the negative log marginal likelihood of the model
  
  Parameters
  ----------
  beta : np.array
      Contains untransformed starting values for latent variables
  
  Returns
  ----------
  The negative log logliklihood of the model
docstr_tok: ["Creates","the","negative","log","marginal","likelihood","of","the","model","Parameters","--","--","--","--","--","beta",":","np.array","Contains","untransformed","starting","values","for","latent","variables","Returns","--","--","--","--","--","The","negative","log","logliklihood","of","the","model"]
code: def neg_loglik(self, beta):
      """Creates the negative log marginal likelihood of the model
  
      Parameters
      ----------
      beta : np.array
          Contains untransformed starting values for latent variables
  
      Returns
      ----------
      The negative log logliklihood of the model
      """
      _, _, _, F, v = self._model(self.y, beta)
      loglik = 0.0
      for i in range(0, self.y.shape[0]):
          loglik += np.linalg.slogdet(F[:, :, i])[1] + np.dot(
              v[i], np.dot(np.linalg.pinv(F[:, :, i]), v[i])
          )
      return -(
          -((self.y.shape[0] / 2) * np.log(2 * np.pi))
          - 0.5 * loglik.T[0].sum()
      )
  
imports: import copy
  import sys
  import numpy
  import pandas
  import scipy.stats
  from patsy import dmatrices, dmatrix, demo_data
  from ..None import families
  from ..None import tsm
  from ..None import data_check
  from .kalman import *
label_desc: Use image node_id 7 for calling the DAR obj's underlying member method code with example usage: obj.neg_loglik(beta) and returns: unknown