code: def corr_ar(k_vars, ar):
      """create autoregressive correlation matrix
  
      This might be MA, not AR, process if used for residual process - check
  
      Parameters
      ----------
      ar : array_like, 1d
          AR lag-polynomial including 1 for lag 0
  
  
      """
      from scipy.linalg import toeplitz
  
      if len(ar) < k_vars:
          ar_ = np.zeros(k_vars)
          ar_[: len(ar)] = ar
          ar = ar_
  
      return toeplitz(ar)
  
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 2 for calling a global function with example usage: corr_ar(k_vars, ar) and returns: toeplitz