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. 
