Cite and acknowledge other RV modeling packages

[barentsen]

In both the JOSS paper and the README/docs, please acknowledge and cite other software packages that enable similar RV analyses. In particular, it is important to clarify exactly what the unique contribution of kima is compared to those other packages.

For example: is kima the first tool to use nested sampling? Is it the first to use GPs? Is it the first to allow the number of planets to vary? Is it faster? Is it more accurate? Are any of these features important? etc, etc...

I'm sure you can think of some key advantages offered by kima. It is important to state clearly what they are. I have opened this issues because the guidelines from the Journal of Open Source Software include the following two requirements:

[The submission] should be a significant contribution to the available open source software that either enables some new research challenges to be addressed or makes addressing research challenges significantly better (e.g., faster, easier, simpler)

Submissions that implement solutions already solved in other software packages are accepted into JOSS provided that they meet the criteria listed above and cite prior similar work.

FYI: Here are the first five alternative packages which I find via Google:
https://github.com/California-Planet-Search/radvel
https://github.com/nespinoza/exonailer
https://github.com/jdeast/EXOFASTv2
https://github.com/oscaribv/pyaneti
https://github.com/mrtommyb/ktransit

(This is part of openjournals/joss-reviews#487.)

[j-faria]

@barentsen, I agree with your suggestion to cite other packages. However, I'm not sure if this should be done in the paper. Is it common in JOSS papers to cite other similar packages? I would be happy to rephrase a bit the text in the paper to highlight kima's key advantages, but I don't think a list of similar packages should be included in the paper.

Regarding the documentation, I added some words here and was thinking of adding something like a "see also" section on the main readme.