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: 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.