Theil-Sen single median method computes slopes of lines crossing all possible pairs
of points, when x coordinates differ. After calculating these n(n-1)/2 slopes (these
value are true only if x is distinct), the median of them is taken as slope estimator.
Next, the intercepts of n lines, crossing each point and having calculated slope are
calculated. The median from them is intercept estimator.
Siegel repeated medians is more complicated. For each point, the slopes between it and
the others are calcuated (resulting n-1 slopes) and the median is taken. This results in
n medians and median from this medians is slope estimator. Intercept is calculated in
similar way, for more information please take a look in function source.
The breakdown point of Theil-Sen method is about 29%, Siegel extended it to 50%,
so these regression methods are very robust. Additionally, if the errors are normally distributed
and no outliers are present, the estimators are very similar to classic least squares.