code: def _yule_walker(X, order=1):
      """Compute Yule-Walker (adapted from statsmodels).
  
      Operates in-place.
      """
      assert X.ndim == 2
      denom = X.shape[-1] - np.arange(order + 1)
      r = np.zeros(order + 1, np.float64)
      for di, d in enumerate(X):
          d -= d.mean()
          r[0] += np.dot(d, d)
          for k in range(1, order + 1):
              r[k] += np.dot(d[0:-k], d[k:])
      r /= denom * len(X)
      rho = linalg.solve(linalg.toeplitz(r[:-1]), r[1:])
      sigmasq = r[0] - (r[1:] * rho).sum()
      return rho, np.sqrt(sigmasq)
  
imports: import numpy
  from scipy import linalg
  from .._fiff.pick import _picks_by_type, _picks_to_idx, pick_info
  from ..defaults import _handle_default
  from ..utils import _apply_scaling_array, verbose
label_desc: Use image node_id 1 for calling a global function with example usage: _yule_walker(X, order) and returns: rho,  np