class_docstr: SARIMAX parameters.
  
  Parameters
  ----------
  spec : SARIMAXSpecification
      Specification of the SARIMAX model.
  
  Attributes
  ----------
  spec : SARIMAXSpecification
      Specification of the SARIMAX model.
  exog_names : list of str
      Names associated with exogenous parameters.
  ar_names : list of str
      Names associated with (non-seasonal) autoregressive parameters.
  ma_names : list of str
      Names associated with (non-seasonal) moving average parameters.
  seasonal_ar_names : list of str
      Names associated with seasonal autoregressive parameters.
  seasonal_ma_names : list of str
      Names associated with seasonal moving average parameters.
  param_names :list of str
      Names of all model parameters.
  k_exog_params : int
      Number of parameters associated with exogenous variables.
  k_ar_params : int
      Number of parameters associated with (non-seasonal) autoregressive
      lags.
  k_ma_params : int
      Number of parameters associated with (non-seasonal) moving average
      lags.
  k_seasonal_ar_params : int
      Number of parameters associated with seasonal autoregressive lags.
  k_seasonal_ma_params : int
      Number of parameters associated with seasonal moving average lags.
  k_params : int
      Total number of model parameters.
docstr: (Polynomial) Seasonal autoregressive lag polynomial.
code: def seasonal_ar_poly(self):
      """(Polynomial) Seasonal autoregressive lag polynomial."""
      # Need to expand the polynomial according to the season
      s = self.spec.seasonal_periods
      coef = [1]
      if s > 0:
          expanded = np.zeros(self.spec.max_seasonal_ar_order)
          ix = np.array(self.spec.seasonal_ar_lags, dtype=int) - 1
          expanded[ix] = -self._params_split["seasonal_ar_params"]
          coef = np.r_[
              1,
              np.pad(
                  np.reshape(expanded, (-1, 1)),
                  [(0, 0), (s - 1, 0)],
                  "constant",
              ).flatten(),
          ]
      return Polynomial(coef)
  
imports: import numpy
  import pandas
  from numpy.polynomial import Polynomial
  from statsmodels.tsa.statespace.tools import is_invertible
  from statsmodels.tsa.arima.tools import validate_basic
label_desc: Use image node_id 14 for calling the SARIMAXParams obj's underlying member method code with example usage: obj.seasonal_ar_poly() and returns: Polynomial