`scipy.stats._mstats_basic:theilslopes`

source: /scipy/stats/_mstats_basic.py:1341

Signature

def theilslopes(y, x = None, alpha = 0.95, method = separate)

Summary

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

Extended Summary

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

Parameters

y : array_like

Dependent variable.

x : array_like or None, optional

Independent variable. If None, use arange(len(y)) instead.

alpha : float, 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".

method : {'joint', 'separate'}, optional

Method to be used for computing estimate for intercept. Following methods are supported,

'joint': Uses np.median(y - slope * x) as intercept.
'separate': Uses np.median(y) - slope * np.median(x)
as intercept.

The default is 'separate'.

Returns

result : ``TheilslopesResult`` instance

The return value is an object with the following attributes:

slope: Theil slope.
intercept: Intercept of the Theil line.
low_slope: Lower bound of the confidence interval on slope.
high_slope: Upper bound of the confidence interval on slope.

Notes

For more details on theilslopes, see scipy.stats.theilslopes.

Aliases

scipy.stats._mstats_basic.theilslopes