The State of Statistics in Julia • Hacker News Board

Re: The State of Statistics in Julia

#11

Post by andrewvc » Mon, Dec 03, 2012, 2:17 AM UTC

StefanKarpinski wrote: post #4

andrewvc wrote: post #3

I tried julia last week looking for an R replacement. I was pretty excited but the web REPL is broken on the current OSX build. Try as I might I could not get the web repl to run when building it myself. It still seems quite immature, but I'm very excited about it's future.

We're phasing out the web repl since it's not actively developed anymore. At some point I'm going to take a crack at providing a Julia backend to iPython Notebook [1]. [1] http://ipython.org/ipython-doc/dev/interactive/htmlnotebook....

That's unfortunate as I was trying to get an r-studio like experience.

Re: The State of Statistics in Julia

#12

Post by StefanKarpinski » Mon, Dec 03, 2012, 2:30 AM UTC

andrewvc wrote: post #11

StefanKarpinski wrote: post #4

Earlier quoted context omitted.

We're phasing out the web repl since it's not actively developed anymore. At some point I'm going to take a crack at providing a Julia backend to iPython Notebook [1]. [1] http://ipython.org/ipython-doc/dev/interactive/htmlnotebook....

That's unfortunate as I was trying to get an r-studio like experience.

No reason that can't happen too, but the current web repl is more of a proof-of-concept.

Re: The State of Statistics in Julia

#13

Post by pseut » Mon, Dec 03, 2012, 5:47 AM UTC

This might be slightly off-topic, but are DataFrames intended to be similar to R's data.frame, where the contents of the entire table are loaded into memory and operated on all at once, or more like SQL with the possibility of aggregate functions calculated incrementally? Since a lot of statistics can be calculated incrementally (OLS, obviously, but even something like MLE based on nonlinear optimization, if you allow for multiple passes through the dataset) R's approach really bugs me... even though providing the right tools for an aggregate function approach would be (I imagine) quite a bit more difficult.

Re: The State of Statistics in Julia

#14

Post by johnmyleswhite » Mon, Dec 03, 2012, 12:08 PM UTC

pseut wrote: post #13

This might be slightly off-topic, but are DataFrames intended to be similar to R's data.frame, where the contents of the entire table are loaded into memory and operated on all at once, or more like SQL with the possibility of aggregate functions calculated incrementally? Since a lot of statistics can be calculated incrementally (OLS, obviously, but even something like MLE based on nonlinear optimization, if you allo…

DataFrames are in-memory. It sounds like you're describing what we're calling DataStreams, which are still a work in progress, but do already exist. And we're also building SGD descent for doing things like OLS incrementally.