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scipy.stats.mstats.

# siegelslopes

scipy.stats.mstats.siegelslopes(y, x=None, method='hierarchical')

  Computes the Siegel estimator 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:
    yarray_like

      Dependent variable.

    xarray_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:

      slopefloat

        Estimate of the slope of the regression line.

      interceptfloat

        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`.