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From "Salman Hussain (JIRA)" <>
Subject [jira] [Comment Edited] (STATISTICS-7) Stream-based Java statistical processing
Date Thu, 28 Mar 2019 00:30:00 GMT


Salman Hussain edited comment on STATISTICS-7 at 3/28/19 12:29 AM:

Hi [~ericbarnhill], I am currently in my 2nd year of studying Computer Science at Imperial
College London and I am interested in this project. I have lots of experience with functional
programming in Java, and additionally have lots of familiarity with Haskell. I also have a
strong knowledge base of statistics but lack experience in R. Would the main aim of the project
to develop libraries of existing statistical methods using Java streams? Thanks!

> Stream-based Java statistical processing
> ----------------------------------------
>                 Key: STATISTICS-7
>                 URL:
>             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
> 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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