class_docstr: Maximum Likelihood Estimation of Linear Model with t-distributed errors
  
  This is an example for generic MLE.
  
  Except for defining the negative log-likelihood method, all
  methods and results are generic. Gradients and Hessian
  and all resulting statistics are based on numerical
  differentiation.
code: def loglike(self, params):
      return -self.nloglikeobs(params).sum(0)
  
file_path: statsmodels/statsmodels/miscmodels/tmodel.py
imports: import numpy
  from scipy import special, stats
  from statsmodels.base.model import GenericLikelihoodModel
  from statsmodels.tsa.arma_mle import Arma
label_desc: Use image node_id 3 for calling the TLinearModel obj's underlying member method code with example usage: obj.loglike(params) and returns: unknown