scipy.stats.mstats.

tsem

scipy.stats.mstats.tsem(a, limits=None, inclusive=(True, True), axis=0, ddof=1)

Compute the trimmed standard error of the mean.

This function finds the standard error of the mean for given values, ignoring values outside the given limits.

Deprecated since version 2.0.0: scipy.stats.mstats.tsem is deprecated as of SciPy 2.0.0 and will be removed, along with the scipy.stats.mstats namespace, in SciPy 2.4.0. For similar functionality, use scipy.stats.tsem with MArray(s) instead of NumPy masked array(s).

Parameters:

aarray_like

array of values

limitsNone or (lower limit, upper limit), optional

Values in the input array less than the lower limit or greater than the upper limit will be ignored. When limits is None, then all values are used. Either of the limit values in the tuple can also be None representing a half-open interval. The default value is None.

inclusive(bool, bool), optional

A tuple consisting of the (lower flag, upper flag). These flags determine whether values exactly equal to the lower or upper limits are included. The default value is (True, True).

axisint or None, optional

Axis along which to operate. If None, compute over the whole array. Default is zero.

ddofint, optional

Delta degrees of freedom. Default is 1.

Returns:

tsemfloat

Notes

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