@property
    def initial_selection(self):
        """Initial selection matrix"""
        if not (self.state_regression and self.time_varying_regression):
            if self.k_posdef > 0:
                selection = np.r_[
                    [0] * (self._k_states_diff),
                    [1] * (self._k_order > 0), [0] * (self._k_order - 1),
                    [0] * ((1 - self.mle_regression) * self.k_exog)
                ][:, None]
            else:
                selection = np.zeros((self.k_states, 0))
        else:
            selection = np.zeros((self.k_states, self.k_posdef))
            # Typical state variance
            if 0 > self._k_order:
                selection[0, 0] = 1
            # Time-varying regression coefficient variances
            for i in range(self.k_exog, 0, -1):
                selection[-i, -i] = 1
        return selection
dataset/ETHPy150Open statsmodels/statsmodels/statsmodels/tsa/statespace/sarimax.py/SARIMAX.initial_selection/swapped operands of `>`