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# 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.

  Parameters:

  a : array_like

  > array of values

  limits : None 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).

  axis : int or None, optional

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

  ddof : int, optional

  > Delta degrees of freedom. Default is 1.

  Returns: | tsem : float

  Notes

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