scipy.stats.mstats.siegelslopes#

scipy.stats.mstats.siegelslopes(y, x=None, method='hierarchical')[source]#

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

Returns

medslopefloat: Estimate of the slope of the regression line.
medinterceptfloat: Estimate of the intercept of the regression line.