ooops...I leaked my signature. not a problem, but it is also was not necessarily what I had meant to say. for those who are interested, here is a little background from my side of the world.
ucla anderson, like most other business schools, has been pretty ignorant with respect to any kind of research computing expertise. this is beginning to change, as management schools (incl us) are moving towards one-year quantitatively oriented one-year masters program. anderson already has a masters of financial engineering and is about to start a masters program in data analytics. as for me, I am also trying to figure out how to offer more of this to MBA students, our traditional bread and butter, but it is not clear whether this can be implemented. so, in the future, we will need more data, programming, and other computing support than we did in the past. like every other industry. it is exceedingly difficult to hire good programmers in a context like our's. universities do not pay much, for institutional reasons. individuals that are very good at this tend to be lured away to industry if they are good, and non-terminable if they are bad. a year goes by very fast---we may find someone for one year, but then not the next. any program has to be prepared to run for decades. we cannot shut down a masters program for lack of a critical person. our current IT department (both UCLA and Anderson) mostly handle basics, such as the network and Microsoft apps. as far as I can tell, http://www.ats.ucla.edu/stat/ offers some R expertise, but not Julia expertise. its depth has varied with the individuals working there. there is no julia support afaik. our best choices are typically individuals that want to get a phd and just happen to have good expertise. R, julia, etc. another choice would be someone who wants to work half-time on a project like julia and the other half-time work on direct program support. job has nice benefits... just to get a position approved can take UC about 3-6 months and is a high-effort affair. we have rules up the wazoo. there is also one month of data expertise that anyone would want to learn (WRDS, CRSP, Compustat). I can spend a month full-time to get there. sigh. so, for the most part, the few of us faculty and phd students, who like programming have been bootstrapping it ourselves. at UCLA Anderson, we are luckier in this respect than many other places (Keith Chen, Peter Rossi, John Mamer, ...), but it's tough. julia expertise would be great for us to have. it would have great externalities for us. if anyone with deep julia expertise wants to apply to UCLA for a few years (phd, undergrad, master), with a side job at Anderson, then drop me an email ;-). for obvious reasons, faculty has and wants no power to make admission decisions (or we would be besieged by our friends and family), but I could put in a good word with our admissions department(s). it matters on the margin. if someone working on julia wants a regular job, also please email me. /iaw ---- Ivo Welch ([email protected]) http://www.ivo-welch.info/ On Wed, Feb 10, 2016 at 2:47 PM, Jeffrey Sarnoff <[email protected]> wrote: > That is a reasonable want; it may take Anderson some time to institute > scholarships for expertise in Julia > If you were already expert with Julia, what would you have your students > doing? > > > for expertThat is a reasonable want. As an alternative, Anderson is > not offering scholarships earmarked for Julia experts. > > On Wednesday, February 10, 2016 at 3:49:47 PM UTC-5, ivo welch wrote: >> >> >> indeed. thank you, josh. I would add a final chapter at >> >> http://docs.julialang.org/en/release-0.4/ >> >> with a set of links to various further resources, examples, full >> stand-alone programs, etc. for me, at least, the perl cookbook and sets of >> self-contained snippet programs to start with, were the main reason why I >> learned perl many years ago. >> >> the key problem to my use of julia over R for my students is that I do >> not have a resident julia expert at UCLA. this won't change anytime soon, >> because they are hard to find (hire) :-(. this google forum is great, but >> it's scary to switch without a double hull. many, many full *working* >> standalone examples are the next best thing for me. >> >> regards, >> >> /iaw >> >> >> ---- >> Ivo Welch ([email protected]) >> http://www.ivo-welch.info/ >> J. Fred Weston Distinguished Professor of Finance >> Anderson School at UCLA, C519 >> Free Finance Textbook, http://book.ivo-welch.info/ >> Exec Editor, Critical Finance Review, >> http://www.critical-finance-review.org/ >> Editor and Publisher, FAMe, http://www.fame-jagazine.com/ >> >> On Wed, Feb 10, 2016 at 10:25 AM, Josh Day <[email protected]> wrote: >> >>> I think a lot of what you're looking for already exists. It's just that >>> things like "run a regression according to variable names" wouldn't belong >>> in base Julia. If you haven't already, I'd take a look at StatsBase.jl, >>> DataFrames.jl, and GLM.jl. >>> >>> >>> http://dataframesjl.readthedocs.org/en/latest/io.html#importing-data-from-tabular-data-files >>> https://github.com/JuliaStats/GLM.jl >>> >>> >>> >>> On Wednesday, February 10, 2016 at 10:58:37 AM UTC-5, ivo welch wrote: >>>> >>>> >>>> ladies and gents---I am not (yet) a julia user. >>>> >>>> may I suggest adding more examples into two places where julia users >>>> will face starting hurdles? >>>> >>>> [1] the I/O docs of julia. like, reading and writing csv files that >>>> are compressed and decompressed on-the-fly, even if not in the ultimate >>>> efficient manner. a large fraction of the time and frustration of new >>>> users is consumed by the task of shoehorning data into and out of new >>>> computer languages. with all of R's problem, the ' d <- read.csv("f.csv")' >>>> and 'd<-read.csv(pipe(paste("gzcat ", fname)))' reduced this entry >>>> frustration greatly. perhaps xml file reading and writing. perhaps... >>>> >>>> [2] more 'standard task' programs would be great. read a csv file, run >>>> a regression according to variable names on the command line, print output, >>>> draw a graph. I know there are fragments throughout the docs, but some >>>> section with ready to run complete programs would be good, perhaps at the >>>> end of the manual. >>>> >>>> in a year, I hope to switch my students from R to julia. >>>> >>>> regards, >>>> >>>> /iaw >>>> >>>> >>
