netsse.tools.misc_func.weighted_std
===================================

.. py:function:: netsse.tools.misc_func.weighted_std(a, w, axis=None, ddof=1)

   Computes the weighted standard deviation of some data.

   The weighted standard deviation is a measure of the spread of a
   distribution of the array elements from the mean, where some of the
   elements are more significant than others. The weighted standard deviation
   is calculated based on the weighted mean and it attaches more importance to
   data that have more weight than to data with less weight
   (National Institute of Standards and Technology, 1996).

   :param a: Variable for which the weighted std. must be computed.
   :type a: array_like
   :param w: Array of weights. All elements must be positive.
             The array ``w`` must broadcastable with the array ``a``.
   :type w: array_like
   :param axis: Axis or axes along which the standard deviation is computed.
                The default is to compute the weighted standard deviation of the
                flattened array.
   :type axis: None or int, optional
   :param ddof: Delta Degrees of Freedom. The divisor used in the calculations is
                ``(N_nz - ddof)/N_nz``, where ``N_nz`` represents the number of
                non-zero weights.
   :type ddof: int, default 0

   :returns: **std** -- Weighted standard deviation of the data.
   :rtype: array_like

   .. seealso::

      :py:obj:`weighted_quantile`
          Computes the `q`-th quantiles of weighted data.

   .. rubric:: References

   National Institute of Standards and Technology, 1996. Formula for the
   weighted standard deviation. Available at:
   https://www.itl.nist.gov/div898/software/dataplot/refman2/ch2/weightsd.pdf
   (Consulted on 06-08-2023).

   .. rubric:: Example

   >>> std = weighted_std(a,w,axis=None,ddof=1)