On 04/12/2017 01:26 PM, Oswin Krause via Boost wrote:
On 2017-04-12 12:34, Bjorn Reese via Boost wrote:
Given that the compression is lossy, I am wondering how it compares with a distribution estimator like:
Simple answer: Histograms are not designed for estimating the quantile function, but the pdf.
The first reference I gave is a distribution (pdf and cdf) estimator.
While it is true that a sufficiently good estimate of the pdf will give you an estimate of the quantiles via the inverse of the cdf, the obtainable precision depends on the size of the bins chosen for the histogram.
On the other hand, if your data is multi-variate or your pdf multi-modal, you will have a hard time using quantiles, while you could still do for example outlier detection using histograms.
Good answer for the quantile estimators.