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# scipy.stats.mstats.hdquantiles

`scipy.stats.mstats.``hdquantiles`(data, prob=[0.25, 0.5, 0.75], axis=None, var=False)

  Computes quantile estimates with the Harrell-Davis method.

  The quantile estimates are calculated as a weighted linear combination of order statistics.

  Parameters: | data : array_like Data array. prob : sequence, optional Sequence of quantiles to compute. axis : int or None, optional Axis along which to compute the quantiles. If None, use a flattened array. var : bool, optional Whether to return the variance of the estimate.
  Returns: | hdquantiles : MaskedArray A (p,) array of quantiles (if var is False), or a (2,p) array of quantiles and variances (if var is True), where `p` is the number of quantiles.