 *y*.  It must have the
            signature ::

                detrend(x: np.ndarray) -> np.ndarray

        normed : bool, default: True
            If ``True``, input vectors are normalised to unit length.

        usevlines : bool, default: True
            Determines the plot style.

            If ``True``, vertical lines are plotted from 0 to the xcorr value
            using `.Axes.vlines`. Additionally, a horizontal line is plotted
            at y=0 using `.Axes.axhline`.

            If ``False``, markers are plotted at the xcorr values using
            `.Axes.plot`.

        maxlags : int, default: 10
            Number of lags to show. If None, will return all ``2 * len(x) - 1``
            lags.

        Returns
        -------
        lags : array (length ``2*maxlags+1``)
            The lag vector.
        c : array  (length ``2*maxlags+1``)
            The auto correlation vector.
        line : `.LineCollection` or `.Line2D`
            `.Artist` added to the Axes of the correlation:

            - `.LineCollection` if *usevlines* is True.
            - `.Line2D` if *usevlines* is False.
        b : `~matplotlib.lines.Line2D` or None
            Horizontal line at 0 if *usevlines* is True
            None *usevlines* is False.

        Other Parameters
        ----------------
        linestyle : `~matplotlib.lines.Line2D` property, optional
            The linestyle for plotting the data points.
            Only used if *usevlines* is ``False``.

        marker : str, default: 'o'
            The marker for plotting the data points.
            Only used if *usevlines* is ``False``.

        data : indexable object, optional
            DATA_PARAMETER_PLACEHOLDER

        **kwargs
            Additional parameters are passed to `.Axes.vlines` and
            `.Axes.axhline` if *usevlines* is ``True``; otherwise they are
            passed to `.Axes.plot`.

        Notes
        -----
        The cross correlation is performed with `numpy.correlate` with
        ``mode = "full"``.
        z