We certainly have some ways to go. I think that matching R is unrealistic, but to start with, having a good working set would be great. I think that John's rework of DataFrames will give us a great push. Also, I am hopeful that with greater demand, more developers will be interested, and that the state of statistics in julia will greatly improve in the 0.4 and 0.5 timeframe.
-viral On Monday, December 15, 2014 12:12:05 AM UTC+5:30, Johan Sigfrids wrote: > > If you just look at the main chapters thing looks pretty good. Julia has > packages for regression, resampling, trees, SVM, PCA, clustering and so on. > But when you start looking into the details of what the packages offer you > find that the Julia offerings are very spars compared to what ISLR uses in > R. > > On Sunday, December 14, 2014 7:10:13 PM UTC+2, [email protected] wrote: >> >> That's interesting. What sort of stuff was not implemented? I would have >> thought (by now) the coverage would be much higher than 30-40%... >> >> >> On Sunday, December 14, 2014 11:07:05 AM UTC-5, Johan Sigfrids wrote: >>> >>> There is a ISLR package for R with a bunch of example datasets used in >>> the book. Those datasets are also available in RDatasets.jl >>> >>> Doing the ISLR example in Julia would involve a lot of writing of >>> functionality. Last summer I browsed through the statistics functionality >>> available in Julia and something like 60-70% of the stuff used in ISLR >>> isn't yet implemented. >>> >>> On Sunday, December 14, 2014 5:41:02 PM UTC+2, John Myles White wrote: >>>> >>>> This would be a great first project for someone interested in learning >>>> Julia. >>>> >>>> FWIW, the RDatasets.jl repo doesn't have anything to do with ISRL -- >>>> except insofar as ISRL decided to use common R datasets. >>>> >>>> -- John >>>> >>>> On Dec 14, 2014, at 10:36 AM, [email protected] wrote: >>>> >>>> I'm going through ISRL and find the book very useful. I see that >>>> someone has loaded the data from the book: >>>> >>>> https://github.com/johnmyleswhite/RDatasets.jl >>>> >>>> >>>> Someone has also taken the chapters in R and implemented in numpy: >>>> >>>> https://github.com/TomAugspurger/StatLearning/tree/master/python >>>> >>>> >>>> The book is great, and I would love to see the examples implemented in >>>> Julia... >>>> >>>> >>>> >>>> >>>>
