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# scipy.stats.mstats.theilslopes

`scipy.stats.mstats.``theilslopes`(y, x=None, alpha=0.95)

  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: | 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”.
  Returns: | medslope : float Theil slope. medintercept : float Intercept of the Theil line, as `median(y) - medslope*median(x)`. lo_slope : float Lower bound of the confidence interval on medslope. up_slope : float Upper bound of the confidence interval on medslope.

  Notes

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