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https://issues.apache.org/jira/browse/STATISTICS-7?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16807976#comment-16807976
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Virendra Singh commented on STATISTICS-7:
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Hey [~ericbarnhill] & [~erans], Even I submitted the draft proposal for
_stat.descriptive.* ._ Is there any other ticket or Am I good here? Because, I
can see the discussion is moved mainly towards _regression_.
But, also , summary statistics is the basic & core of Statistics so I think I'm
at right place.
Also, I'm waiting for feedback on draft proposal, [~ericbarnhill] . Tell me if
any changes to make.
> Stream-based Java statistical processing
> ----------------------------------------
>
> Key: STATISTICS-7
> URL: https://issues.apache.org/jira/browse/STATISTICS-7
> Project: Apache Commons Statistics
> Issue Type: New Feature
> Reporter: Eric Barnhill
> Priority: Major
> Labels: GSoC2019, gsoc2019, statistics, streams
>
> The new component aims to be a library of commons statistics functions
> synchronized with the latest developments in the Java language, in particular
> Java's functional programming syntax.
> The library will make commonly used statistical functions available to an end
> user through a simple grammar comparable to commons-math-statistics or
> scikit-learn, while under the hood will implement Java's mapping, streaming,
> and other producer and consumer functions to ensure the statistical methods
> run optimally in new Java implementations.
> Developers working on the project will have the opportunity to demonstrate
> Java programming, functional programming, algorithm design, and data science
> skills and receive authorship on a commons project that is likely to be
> widely used.
> The ideal contributor will also be able to help with important architectural
> decision making. The old source of these libraries, commons-math, grew too
> large, hierarchically complex and interdependent for the commons mission. The
> developers on this project need to make architectural choices that will
> enable the statiscal code to be lightweight and reusable, with a minimum of
> outside dependencies while avoiding redundancy.
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