[ACCEPTED]-Is there any statistical library for javascript?-javascript
OpenEpi is a Javascript stats library, is open 25 source, and has ANOVA and t-tests. I've 24 not tried it (it's a bit too focused on 23 epidemiology for my needs) but it might 22 be useful.
jStat is a javascript statistical library 21 project, and it looks like it's got a great 20 future, but it might not have all you need 19 right now. Edit: as of Dec 2012 it looks like 18 the jStat project page is no longer maintained 17 but the project is continuing to be developed. There's 16 more up to date documentation on github. It now does have anova tests and varieties of t-test. No sign of 15 Wilcoxon signed-rank though.
If you need 14 very specific statistical processing in 13 javascript urgently, you might have most 12 success by browsing Omegahat who have various little 11 tools that bridge the established stats 10 language R with others including javascript.
It'll 9 depend on the details of exactly what you 8 want to do, but you might have some success with 7 packages such as RJavascript - a code translator which 6 aims to help turn existing R features into 5 Javascript (just don't expect quality results 4 first time). Also, SpiderMonkey builds on R for browsers, so 3 it might be useful for internal or personal 2 uses (but it's unlikely to be suitable for 1 public publishing).
Some years ago I ported https://code.google.com/p/statistics-distributions-js/ so that I could 2 use it in http://elem.com/~btilly/effective-ab-testing/ - it may have the functionality 1 you need if you only need simple things.
If you're looking for a simple library for 2 descriptive statistics, you could use javascriptstats.com
It 1 does:
- Mean
- Median
- Mode
- Range
- Variance
- Standard Deviation
Best!
Leveraging a related answer:
The following 8 blog post lists some recent packages: http://jgoodall.me/posts/2012/02/01/javascript-statistical-libraries/
As 7 mentioned by others, native JS is a far 6 cry from R, which web-wise has progressed 5 from RApache (http://rapache.net/) to shiny (http://www.rstudio.com/shiny/). The latter 4 uses node.js server-side, so this is quite 3 promising. Of course both approaches will 2 require you to code stats in R server-side, instead 1 of using JS either on client or server.
Marc
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