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https://issues.apache.org/jira/browse/STATISTICS-7?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16801176#comment-16801176
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VIRENDRA SINGH edited comment on STATISTICS-7 at 3/25/19 10:18 PM:
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Hi [~erans]/[~ericbarnhill], I am Virendra Singh and I am interested in this
project.To be clear I want to work on this project under GSoC 2019.I am
currently studying Business analytics and Data science.
From the description I understood that we are using Functional Interfaces from
Java 8 for developing this statistics library.I also saw some statistical
functions already programmed like chi-square distribution,Gamma
Distribution,Normal Distribution etc.
My question is ,for this project do we have to code more statistical function
or anything else?Also, if I've understood anything wrong please correct me.
was (Author: virendrasinghrp):
Hi [~erans], I am Virendra Singh and I am interested in this project.To be
clear I want to work on this project under GSoC 2019.I am currently studying
Business analytics and Data science.
From the description I understood that we are using Functional Interfaces from
Java 8 for developing this statistics library.I also saw some statistical
functions already programmed like chi-square distribution,Gamma
Distribution,Normal Distribution etc.
My question is ,for this project do we have to code more statistical function
or anything else?Also, if I've understood anything wrong please correct me.
> 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.
>
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