# 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.

  See also

  `hdquantiles_sd`