def fit(self, y: np.ndarray, X: Optional[np.ndarray] = None):
        """Fit the AutoARIMA estimator
        Fit an AutoARIMA to a time series (numpy array) `y`
        and optionally exogenous variables (numpy array) `X`.

        Parameters
        ----------
        y: array-like of shape (n,)
            One-dimensional numpy array of floats without `np.nan` or `np.inf`
            values.
        X: array-like of shape (n, n_x) optional (default=None)
            An optional 2-d numpy array of exogenous variables (float).
        """
        model_ = auto_arima_f(
            x=y,
            d=self.d,
            D=self.D,
            max_p=self.max_p,
            max_q=self.max_q,
            max_P=self.max_P,
            max_Q=self.max_Q,
            max_order=self.max_order,
            max_d=self.max_d,
            max_D=self.max_D,
            start_p=self.start_p,
            start_q=self.start_q,
            start_P=self.start_P,
            start_Q=self.start_Q,
            stationary=self.stationary,
            seasonal=self.seasonal,
            ic=self.ic,
            stepwise=self.stepwise,
            nmodels=self.nmodels,
            trace=self.trace,
            approximation=self.approximation,
            method=self.method,
            truncate=self.truncate,
            xreg=X,
            test=self.test,
            test_kwargs=self.test_kwargs,
            seasonal_test=self.seasonal_test,
            seasonal_test_kwargs=self.seasonal_test_kwargs,
            allowdrift=self.allowdrift,
            allowmean=self.allowmean,
            blambda=self.blambda,
            biasadj=self.biasadj,
            period=self.period,
        )
        self.model_ = ARIMASummary(model_)

        return self
Fit the AutoARIMA estimator
        Fit an AutoARIMA to a time series (numpy array) `y`
        and optionally exogenous variables (numpy array) `X`.

        Parameters
        ----------
        y: array-like of shape (n,)
            One-dimensional numpy array of floats without `np.nan` or `np.inf`
            values.
        X: array-like of shape (n, n_x) optional (default=None)
            An optional 2-d numpy array of exogenous variables (float).
        
python/statsforecast/arima.py