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 predict(self, params, exog=None):
      if exog is None:
          exog = self.exog
      return np.dot(exog, params[: self.exog.shape[1]])
  
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 5 for calling the TLinearModel obj's underlying member method code with example usage: obj.predict(params, exog) and returns: np