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https://issues.apache.org/jira/browse/STATISTICS-7?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16801653#comment-16801653
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Gilles commented on STATISTICS-7:
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Some of the "Commons Math" open issues stem from design bugs (e.g. MATH-1281).
The new component allows to start from a clean slate, without the
backward-compatibility constraint, hopefully with design lessons learnt from
other libraries, and from mistakes made in "Commons Math" whose fix have been
delayed indefinitely.
Indeed, the design of the {{stat}} package dates from the inception of the
component, back in 2003: In the [initial
proposal|http://commons.apache.org/proper/commons-math/proposal.html], half of
the source description pertains to statistics and from those, the random
utilities have gone into their [own
component|http://commons.apache.org/proper/commons-rng/] which I consider as a
step in the right direction, i.e. away from a huge monolithic library that
proved to be an unsustainable project, mostly because requested stability of
some packages prevented a sane evolution of others (solely because they were
part of the same component!).
That said, an advantage to having "Commons Math" is that a lot of the "core"
codes and unit tests can be leveraged for making the port work relatively fast
and robust, once a new design has been put forward. And if there are competing
proposals, they can be developed in parallel, for some time, until one seems to
gather more interest.
> 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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