`scipy.stats._mstats_extras:trimmed_mean_ci`

source: /scipy/stats/_mstats_extras.py :213

Signature

   def     trimmed_mean_ci (    data    ,    limits    =  (0.2, 0.2)   ,    inclusive    =  (True, True)   ,    alpha    =  0.05   ,    axis    =  None     )

Summary

Selected confidence interval of the trimmed mean along the given axis.

Parameters

data : array_like

Input data.

limits : {None, tuple}, optional

None or a two item tuple. Tuple of the percentages to cut on each side of the array, with respect to the number of unmasked data, as floats between 0. and 1. If n is the number of unmasked data before trimming, then (n * limits[0])th smallest data and (n * limits[1])th largest data are masked. The total number of unmasked data after trimming is n * (1. - sum(limits)). The value of one limit can be set to None to indicate an open interval.

Defaults to (0.2, 0.2).

inclusive : (2,) tuple of boolean, optional

If relative==False, tuple indicating whether values exactly equal to the absolute limits are allowed. If relative==True, tuple indicating whether the number of data being masked on each side should be rounded (True) or truncated (False).

Defaults to (True, True).

alpha : float, optional

Confidence level of the intervals.

Defaults to 0.05.

axis : int, optional

Axis along which to cut. If None, uses a flattened version of data.

Defaults to None.

Returns

trimmed_mean_ci : (2,) ndarray: The lower and upper confidence intervals of the trimmed data.

Aliases

scipy.stats._mstats_extras.trimmed_mean_ci