scipy.stats.mstats.theilslopes¶

scipy.stats.mstats.theilslopes(y, x=None, alpha=0.95)[source]¶

Computes the Theil-Sen estimator for a set of points (x, y).

theilslopes implements a method for robust linear regression. It computes the slope as the median of all slopes between paired values.

Parameters

yarray_like: Dependent variable.
xarray_like or None, optional: Independent variable. If None, use arange(len(y)) instead.
alphafloat, optional: Confidence degree between 0 and 1. Default is 95% confidence. Note that alpha is symmetric around 0.5, i.e. both 0.1 and 0.9 are interpreted as “find the 90% confidence interval”.

Returns

medslopefloat: Theil slope.
medinterceptfloat: Intercept of the Theil line, as median(y) - medslope*median(x).
lo_slopefloat: Lower bound of the confidence interval on medslope.
up_slopefloat: Upper bound of the confidence interval on medslope.