code: def __init__(self, method="mle"):
      if method == "mle":
          self.params = [
              0.810898877154,
              -0.535753742985,
              0.101765385197,
              -0.691891368356,
          ]
          self.aic = 756.286535543453
          self.bic = 773.893840132765
          self.arroots = [0.7568 - 1.1375j, 0.7568 + 1.1375j]
          self.maroots = [-1.1309, 1.2780]
          self.bse = [
              0.065073834100,
              0.060522519771,
              0.065569474599,
              0.071275323591,
          ]
          self.cov_params = [
              [0.0042346, -0.0012416, -0.0024319, -0.0012756],
              [-0.0012416, 0.0036630, -0.00022460, -0.0019999],
              [-0.0024319, -0.00022460, 0.0042994, 0.0017842],
              [-0.0012756, -0.0019999, 0.0017842, 0.0050802],
          ]
          self.hqic = 763.372960386513
          self.llf = -373.143267771727
          self.resid = resids_mle[:, 3]
          self.fittedvalues = yhat_mle[:, 3]
          self.pvalues = [1.22e-35, 8.59e-19, 0.1207, 2.81e-22]
          self.tvalues = [12.46, -8.852, 1.552, -9.707]
          self.sigma2 = 1.069529754715**2
      elif method == "css":
          self.params = [
              0.811172493623,
              -0.538952207139,
              0.108020549805,
              -0.697398037845,
          ]
          self.aic = 749.652327535412
          self.bic = 767.219471266237
          self.arroots = [0.7525 - 1.1354j, 0.7525 + 1.1354j]
          self.maroots = [-1.1225 + 0.0000j, 1.2774 + 0.0000j]
          # NOTE: bse, cov_params, tvalues taken from R; commented-out
          #   versions below are from [TODO: finish this sentence]
          # self.bse = [0.063356402845, 0.064719801680, 0.058293106832,
          #             0.061453528114]
          self.bse = [0.06549657, 0.06127495, 0.06514116, 0.07148213]
          # self.cov_params = [
          #   [0.0040140, -0.0016670, -0.0019069, -0.0011369],
          #   [-0.0016670, 0.0041887, -0.00019356, -0.0014322],
          #   [-0.0019069, -0.00019356, 0.0033981, 0.0020063],
          #   [-0.0011369, -0.0014322, 0.0020063, 0.0037765]]
          self.cov_params = [
              [0.004289801, -0.0012980774, -0.0024461381, -0.001244467],
              [-0.001298077, 0.0037546193, -0.0001725373, -0.002039177],
              [-0.002446138, -0.0001725373, 0.0042433713, 0.001720042],
              [-0.001244467, -0.0020391767, 0.0017200417, 0.005109695],
          ]
          self.hqic = 756.724194601530
          self.llf = -369.826163767706
          self.resid = resids_css[2:, 3]
          self.fittedvalues = yhat_css[2:, 3]
          self.pvalues = [1.57e-37, 8.26e-17, 0.0639, 7.55e-30]
          # self.tvalues = [12.80, -8.327, 1.853, -11.35]
          self.tvalues = [12.385077, -8.795883, 1.657944, -9.755738]
          self.sigma2 = 1.074973483083**2
  
imports: import os
  from numpy import genfromtxt
label_desc: Use image node_id 1 to create a new Y_arma22 object  with example: obj = Y_arma22(method)