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

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.

See also

hdquantiles_sd

scipy.stats.mstats.hdmedian scipy.stats.mstats.hdquantiles_sd