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From "Phil Steitz (JIRA)" <j...@apache.org>
Subject [jira] [Resolved] (MATH-418) add a storeless version of Percentile
Date Sat, 21 Jun 2014 18:22:25 GMT

     [ https://issues.apache.org/jira/browse/MATH-418?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Phil Steitz resolved MATH-418.
------------------------------

       Resolution: Fixed
    Fix Version/s:     (was: 4.0)
                   3.4

30-may patch with the following modifications committed in r 1604443:
* Changed class names to "PSquare" to match references
* Changed default quantile to 50 to be consistent with Percentile
* Changed some hashcode implementations to use jdk Arrays.hashcode
* Extracted constants to avoid repeated initialization (low, high marker indexes)
* Changed random data tests to use a fixed seed
* Miscellaneous javadoc edits

Thanks for the patch!

> add a storeless version of Percentile
> -------------------------------------
>
>                 Key: MATH-418
>                 URL: https://issues.apache.org/jira/browse/MATH-418
>             Project: Commons Math
>          Issue Type: New Feature
>    Affects Versions: 2.1
>            Reporter: Luc Maisonobe
>             Fix For: 3.4
>
>         Attachments: 30-may-2014-418-psquare-patch, 418-psquare-patch, psquare-patch
>
>
> The Percentile class can handle only in-memory data.
> It would be interesting to use an on-line algorithm to estimate quantiles as a storeless
statistic.
> An example of such an algorithm is the exponentially weighted stochastic approximation
 described in a 2000 paper by Fei Chen ,  Diane Lambert  and José C. Pinheiro "Incremental
Quantile Estimation for Massive Tracking" which can be retrieved from CiteSeerX at [http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.105.1580].



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