class_docstr: Empirical Likelihood inference and estimation for linear regression
  through the origin.
  
  Parameters
  ----------
  endog: nx1 array
      Array of response variables.
  
  exog: nxk array
      Array of exogenous variables.  Assumes no array of ones
  
  Attributes
  ----------
  endog : nx1 array
      Array of response variables
  
  exog : nxk array
      Array of exogenous variables.  Assumes no array of ones.
  
  nobs : float
      Number of observations.
  
  nvar : float
      Number of exogenous regressors.
code: def __init__(self, endog, exog):
      self.endog = endog
      self.exog = exog
      self.nobs = self.exog.shape[0]
      try:
          self.nvar = float(exog.shape[1])
      except IndexError:
          self.nvar = 1.0
  
file_path: statsmodels/statsmodels/emplike/originregress.py
imports: import numpy
  from scipy import optimize
  from scipy.stats import chi2
  from statsmodels.regression.linear_model import OLS, RegressionResults
  from statsmodels.tools.tools import add_constant
label_desc: Use image node_id 1 to create a new ELOriginRegress object  with example: obj = ELOriginRegress(endog, exog)