code: def yule_walker_acov(
      acov, order=1, method="unbiased", df=None, inv=False
  ):
      """
      Estimate AR(p) parameters from acovf using Yule-Walker equation.
  
  
      Parameters
      ----------
      acov : array_like, 1d
          auto-covariance
      order : int, optional
          The order of the autoregressive process.  Default is 1.
      inv : bool
          If inv is True the inverse of R is also returned.  Default is False.
  
      Returns
      -------
      rho : ndarray
          The estimated autoregressive coefficients
      sigma
          TODO
      Rinv : ndarray
          inverse of the Toepliz matrix
      """
      return yule_walker(
          acov, order=order, method=method, df=df, inv=inv, demean=False
      )
  
file_path: statsmodels/statsmodels/sandbox/panel/correlation_structures.py
imports: import numpy
  from statsmodels.regression.linear_model import yule_walker
  from statsmodels.stats.moment_helpers import cov2corr
label_desc: Use image node_id 6 for calling a global function with example usage: yule_walker_acov(acov, order, method, df, inv) and returns: yule_walker