code: def get_a(values, n):
          
          m = len(values)-n
          a = numpy.empty((m, n), dtype=float)
          for i in range(m):
              i0 = i-1 if i > 0 else None
              i1 = i+n-1
              a[i] = values[i1:i0:-1]
          return numpy.array(a)
docs: Extract the independent variables of the given values and return
          them as a matrix with n columns in a form suitable for the least
          squares approach applied in method |ARMA.update_ar_coefs|.