class_docstr: Short Panel with general intertemporal within correlation
  
  assumes data is stacked by individuals, panel is balanced and
  within correlation structure is identical across individuals.
  
  It looks like this can just inherit GLS and overwrite whiten
class_docstr_tok: ["Short","Panel","with","general","intertemporal","within","correlation","assumes","data","is","stacked","by","individuals",",","panel","is","balanced","and","within","correlation","structure","is","identical","across","individuals",".","It","looks","like","this","can","just","inherit","GLS","and","overwrite","whiten"]
code: def _fit_old(self):
      # old explicit version
      res_pooled = self._fit_ols()  # get starting estimate
      sigma_i = self.get_within_cov(res_pooled.resid)
      self.cholsigmainv_i = np.linalg.cholesky(
          np.linalg.pinv(sigma_i)
      ).T
      wendog = self.whiten_groups(self.endog, self.cholsigmainv_i)
      wexog = self.whiten_groups(self.exog, self.cholsigmainv_i)
      self.res1 = OLS(wendog, wexog).fit()
      return self.res1
  
imports: import numpy
  from statsmodels.regression.linear_model import OLS, GLS
  from statsmodels.tools.grouputils import GroupSorted
label_desc: Use image node_id 5 for calling the ShortPanelGLS obj's underlying member method code with example usage: obj._fit_old() and returns: self