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:

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 medslope (default option). If ‘separate’, estimate the intercept independent of the estimated slope. See Notes for details.

Returns:

medslope : float

Estimate of the slope of the regression line.

medintercept : 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.