code: def __init__(self, method="mle"):
      if method == "mle":
          self.params = [
              4.562207236168,
              0.754284447885,
              -0.305849188005,
              0.253824706641,
              0.281161230244,
              -0.172263847479,
          ]
          self.aic = 711.817562780112
          self.bic = 736.467789205148
          self.arroots = [
              -1.6535 + 0.0j,
              0.0129 - 1.2018j,
              0.0129 + 1.2018j,
              1.1546 + 0.0j,
              2.1052 + 0j,
          ]
          self.maroots = None
          self.bse = [
              0.318447388812,
              0.062272737541,
              0.076600312879,
              0.077310728819,
              0.076837326995,
              0.062642955733,
          ]
          self.cov_params = [
              [
                  0.10141,
                  -6.6930e-05,
                  -7.3157e-05,
                  -4.4815e-05,
                  7.7676e-05,
                  -0.00013170,
              ],
              [
                  -6.6930e-05,
                  0.0038779,
                  -0.0028465,
                  0.0013770,
                  -0.0012194,
                  -0.00058978,
              ],
              [
                  -7.3157e-05,
                  -0.0028465,
                  0.0058676,
                  -0.0040145,
                  0.0024694,
                  -0.0012307,
              ],
              [
                  -4.4815e-05,
                  0.0013770,
                  -0.0040145,
                  0.0059769,
                  -0.0040413,
                  0.0013481,
              ],
              [
                  7.7676e-05,
                  -0.0012194,
                  0.0024694,
                  -0.0040413,
                  0.0059040,
                  -0.0028575,
              ],
              [
                  -0.00013170,
                  -0.00058978,
                  -0.0012307,
                  0.0013481,
                  -0.0028575,
                  0.0039241,
              ],
          ]
          self.hqic = 721.738557560396
          self.llf = -348.908781390056
          self.resid = residsc_mle[:, 4]
          self.fittedvalues = yhatc_mle[:, 4]
          self.pvalues = [
              1.50e-46,
              9.06e-34,
              6.53e-05,
              0.0010,
              0.0003,
              0.0060,
          ]
          self.tvalues = [14.33, 12.11, -3.993, 3.283, 3.659, -2.750]
          self.sigma2 = 0.973930886014**2
          self.forecast = forecast_results["fc50c"]
          self.forecasterr = forecast_results["fe50c"]
      elif method == "css":
          # NOTE: params, bse, cov_params, tvalues taken from R;
          #   commented-out versions below are from
          #   [TODO: Finish this sentence]
          # likelihood based results from x-12 arima
          # self.params = [0.843173779572, 0.755433266689, -0.296886816205,
          #                0.253572751789, 0.276975022313, -0.172637420881]
          self.params = [
              4.593494860193,
              0.755427402630,
              -0.296867127441,
              0.253556723526,
              0.276987447724,
              -0.172647993470,
          ]
          # self.aic = 694.843378847617
          self.aic = 696.8434
          # self.bic = 715.850928110886
          self.bic = 721.3522
          self.arroots = [
              -1.6539 + 0.0000j,
              0.0091 - 1.2069j,
              0.0091 + 1.2069j,
              1.1508 + 0.0000j,
              2.0892 + 0.0000j,
          ]
          self.maroots = None
          # self.bse = [0.236922950898, 0.063573574389, 0.078206936773,
          #             0.078927252266, 0.078183651496, 0.063596048046]
          self.bse = [
              0.3359627893565,
              0.0621593755265,
              0.0764672280408,
              0.0771715117870,
              0.0764444608104,
              0.0621813373935,
          ]
          # self.cov_params = [
          #   [0.056132, -0.0028895, -0.0012291,
          #    -0.0031424, -0.0012502, -0.0028739],
          #   [-0.0028895, 0.0040416, -0.0029508,
          #    0.0014229, -0.0012546, -0.00062818],
          #   [-0.0012291, -0.0029508, 0.0061163,
          #    -0.0041939, 0.0025537, -0.0012585],
          #   [-0.0031424, 0.0014229, -0.0041939,
          #    0.0062295, -0.0041928, 0.0014204],
          #   [-0.0012502, -0.0012546, 0.0025537,
          #    -0.0041928, 0.0061127, -0.0029479],
          #   [-0.0028739, -0.00062818, -0.0012585,
          #    0.0014204, -0.0029479, 0.0040445]
          # ]
          self.cov_params = [
              [
                  1.12870995832e-01,
                  4.32810158586e-05,
                  -1.89697385245e-05,
                  0.0000465331836881,
                  -0.000024151327384,
                  0.000109807500875,
              ],
              [
                  4.32810158586e-05,
                  3.86378796585e-03,
                  -2.82098637123e-03,
                  0.001360256141301,
                  -0.001199382243647,
                  -0.000600542191229,
              ],
              [
                  -1.89697385245e-05,
                  -2.82098637123e-03,
                  5.84723696424e-03,
                  -0.004009391809667,
                  0.002441359768335,
                  -0.001203154760767,
              ],
              [
                  4.65331836880e-05,
                  1.36025614130e-03,
                  -4.00939180967e-03,
                  0.005955442231484,
                  -0.004008307295820,
                  0.001357917028471,
              ],
              [
                  -2.41513273840e-05,
                  -1.19938224365e-03,
                  2.44135976834e-03,
                  -0.004008307295820,
                  0.005843755588588,
                  -0.002818181279545,
              ],
              [
                  1.09807500875e-04,
                  -6.00542191229e-04,
                  -1.20315476077e-03,
                  0.001357917028471,
                  -0.002818181279545,
                  0.003866518720043,
              ],
          ]
          # self.hqic = 703.303100827167
          self.hqic = 706.7131
          self.llf = -341.421689423809
          self.resid = residsc_css[5:, 4]
          self.fittedvalues = yhatc_css[5:, 4]
          self.pvalues = [
              0.0004,
              1.45e-32,
              0.0001,
              0.0013,
              0.0004,
              0.0066,
          ]
          # self.tvalues = [3.559, 11.88, -3.796, 3.213, 3.543, -2.715]
          self.tvalues = [
              13.67262984389,
              12.15307258528,
              -3.88227918086,
              3.28562597329,
              3.62338153462,
              -2.77652428699,
          ]
          # self.sigma2 = 0.987100631424**2
          self.sigma2 = 0.974939**2
  
imports: import os
  from numpy import genfromtxt
label_desc: Use image node_id 1 to create a new Y_arma50c object  with example: obj = Y_arma50c(method)