bundles / scipy 1.17.1 / scipy / stats / _mstats_basic / trimmed_stde
function
scipy.stats._mstats_basic:trimmed_stde
Signature
def trimmed_stde ( a , limits = (0.1, 0.1) , inclusive = (1, 1) , axis = None ) Summary
Returns the standard error of the trimmed mean along the given axis.
Parameters
a: sequenceInput array
limits: {(0.1,0.1), tuple of float}, optionaltuple (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 thann * `limits[1]are masked, and the total number of unmasked data after trimming isn * (1.-sum(limits)). In each case, the value of one limit can be set to None to indicate an open interval. Iflimitsis None, no trimming is performed.inclusive: {(bool, bool) tuple} optionalTuple indicating whether the number of data being masked on each side should be rounded (True) or truncated (False).
axis: int, optionalAxis along which to trim.
Returns
trimmed_stde: scalar or ndarray
Aliases
-
scipy.stats._mstats_basic.trimmed_stde