scipy.stats.mstats.

trimmed_stde

scipy.stats.mstats.trimmed_stde(a, limits=(0.1, 0.1), inclusive=(1, 1), axis=None)

Returns the standard error of the trimmed mean along the given axis.

Deprecated since version 2.0.0: scipy.stats.mstats.trimmed_stde is deprecated as of SciPy 2.0.0 and will be removed, along with the scipy.stats.mstats namespace, in SciPy 2.4.0. SciPy offers no replacement for this function. See the Trimming and winsorization transition guide for alternatives.

Parameters:

asequence

Input array

limits{(0.1,0.1), tuple of float}, optional

tuple (lower percentage, upper percentage) to cut on each side of the array, with respect to the number of unmasked data.

If n is the number of unmasked data before trimming, the values smaller than n * limits[0] and the values larger than n * `limits[1] are masked, and the total number of unmasked data after trimming is n * (1.-sum(limits)). In each case, the value of one limit can be set to None to indicate an open interval. If limits is None, no trimming is performed.

inclusive{(bool, bool) tuple} optional

Tuple indicating whether the number of data being masked on each side should be rounded (True) or truncated (False).

axisint, optional

Axis along which to trim.

Returns:

trimmed_stdescalar or ndarray