imator for a set of points (x, y).

`siegelslopes` implements a method for robust linear regression
using repeated medians to fit a line to the points (x, y).
The method is robust to outliers with an asymptotic breakdown point
of 50%.

Parameters
----------
y : array_like
    Dependent variable.
x : array_like or None, optional
    Independent variable. If None, use ``arange(len(y))`` instead.
method : {'hierarchical', 'separate'}
    If 'hierarchical', estimate the intercept using the estimated
    slope ``slope`` (default option).
    If 'separate', estimate the intercept independent of the estimated
    slope. See Notes for details.

Returns
-------
result : ``SiegelslopesResult`` instance
    The return value is an object with the following attributes:

    slope : float
        Estimate of the slope of the regression line.
    intercept : float
        Estimate of the intercept of the regression line.

See Also
--------
theilslopes : a similar technique without repeated medians

Notes
-----
For more details on `siegelslopes`, see `scipy.stats.siegelslopes`.

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