Boost logo

Boost :

Subject: Re: [boost] [proposed][histogram]
From: Bjorn Reese (breese_at_[hidden])
Date: 2017-04-12 11:58:25


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:
>>
>> https://arxiv.org/abs/1507.05073v2

> 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.


Boost list run by bdawes at acm.org, gregod at cs.rpi.edu, cpdaniel at pacbell.net, john at johnmaddock.co.uk