scipy.stats.mstats.hdquantiles#

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

Computes quantile estimates with the Harrell-Davis method.

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

Parameters:

dataarray_like: Data array.
probsequence, optional: Sequence of quantiles to compute.
axisint or None, optional: Axis along which to compute the quantiles. If None, use a flattened array.
varbool, optional: Whether to return the variance of the estimate.

Returns:

hdquantilesMaskedArray: 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.