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turn the Bayesian vignette trilogy into a JOSE paper #439

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IndrajeetPatil opened this issue Jun 30, 2021 · 4 comments
Open
4 tasks

turn the Bayesian vignette trilogy into a JOSE paper #439

IndrajeetPatil opened this issue Jun 30, 2021 · 4 comments
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Docs 📚 Add or improve docstrings and vignettes High priority 🏃 This issue should be addressed soon

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@IndrajeetPatil
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IndrajeetPatil commented Jun 30, 2021

https://jose.theoj.org/

Reminder for self, once this is published, just provide citation for the paper and redirect readers to the article webpage for the following vignettes:

  • Get Started with Bayesian Analysis
  • Initiation to Bayesian models
  • Confirmation of Bayesian skills
  • Become a Bayesian master

P.S. Another option for publication outlet:
https://openresearchsoftware.metajnl.com/about/

@IndrajeetPatil IndrajeetPatil added Docs 📚 Add or improve docstrings and vignettes High priority 🏃 This issue should be addressed soon labels Jun 30, 2021
@IndrajeetPatil IndrajeetPatil pinned this issue Jun 30, 2021
@bwiernik
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This sounds like a great idea. I can add a bit of a frequentist/fiducial/error-statistical lens to it too

IndrajeetPatil added a commit that referenced this issue Jul 20, 2021
@mattansb mattansb unpinned this issue Aug 10, 2021
@IndrajeetPatil
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@humanfactors Hi Michael! 👋

Will you be interested in working on this with us? Given that the vignettes are already there, it's just a matter of stitching them together to create a coherent tutorial paper.

WDYT? ☺️

@humanfactors
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humanfactors commented Aug 2, 2022

Hi @IndrajeetPatil , I certainly am interested in providing contributions to this paper! Thank you kindly for the invitation. 😊

There will naturally be some challenge in terms of stitching the sections together to ensure consistency, and I hope this is something I can contribute to in this regard.

I'm curious as to what scope we are aiming for, as I'm not deeply familiar with JOSE. Is this borderline a tutorial-style paper (similar to the posts I assume)? I ask this because I do wonder how much more detail may or may not be needed regarding the mechanics of Bayesian analysis and sampling etc.

In any case, please keep me updated how I can best contribute and look forward to further discussions!

@IndrajeetPatil
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Thanks for your response, and I am glad to know that you will be interested in contributing to this!

As for the scope, we want this to be a beginner-friendly tutorial on how to do Bayesian analysis, with the keys concepts illustrated using the {bayestestR} package functionality. Does that make sense (cc @DominiqueMakowski)?

For more about JOSE, see: https://jose.theoj.org/about

I had already set up a skeleton here, which can be a good starting point. Needless to say, all author details there are placeholders, and we can revisit this later :)

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