Data Science. TileDB. Open Source. Quant Research. R. C++. Debian. Linux. Adjunct Clinical Professor, University of Illinois. Lots of coffee. And some running.

Chicago, IL, USA
Joined March 2007
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"There are two types of dichotomy: False dichotomies, true dichotomies, and surprise trichotomies."
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dtts 0.1.0 on CRAN: New Package data.table time series ops at nanosecond resolution dirk.eddelbuettel.com/blog/2… #rstats #rcpp Think `xts` but at nanosecond resolution. All the immense power of `data.table` at the hightest time resolution.
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Replying to @KatherineSliter
You could try my course, it often gets PhD students from neighbouring departments. The course slides are up (and the videos are for Illinois students) and there are additional resources per topic on the course site: stat447.com
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Reposting as 'live monitoring' of markets remains a timely topic given the recent changes---and the corresponding update of #RStats package `RcppRedis` is now on CRAN. And of course #notowarwithukraine
R^4 Post #036: pub/sub with Redis and R Real-time financial market monitoring with R and Redis dirk.eddelbuettel.com/blog/2… #rstats #rcpp #redis But special thanks to @joshua_ulrich and especially (twitterless) Bryan Lewis
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RcppRedis 0.2.0 on CRAN: Major Updates Performant R interface to Redis dirk.eddelbuettel.com/blog/2… #rstats #rcpp With lovely new code for pub/sub with @Redisinc, two examples for pub/sub for (financial) market monitoring, and two new vignettes.
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Which has the added advantage of already working today with the released version of #RStats 😀
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Nice indeed. But then lm(mpg ~ disp, data = mtcars, subset = cyl==4) is still shorter, and quite possibly more readable. 😉 #rstats
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nanotime 0.3.6 on CRAN: Updates High-resolution nanosecond time functionality for R dirk.eddelbuettel.com/blog/2… #rcpp #rstats
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Replying to @bernhardsson
It's a different context (i.e. our focus is within R), but we had something to day about the resulting complexity: tinyverse.org/ Simpler can be better / is often better. But for just about everything, tradeoffs exists, and need to be managed.
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If you want to learn about #Rcpp for C++ and #Rstats integration, I will be giving a one-hour introduction on March 25 thanks to a kind invitation by @NISS_DataSci via Kevin Lee. Registration should be opening soon, more details at the link below. niss.org/events/rcpp-r-and-c…
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oh and of course gaussfacts::gaussfact() !!
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Replying to @datavisFriendly
Suggestions: - wrap if (interactive()) around the call - randomly sample from statsquotes::statquote(), fortunes::fortune() and dang::demotiveate() to spice up your #rstats use
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Replying to @jntrcs
A few of us put this together last year: ess-intro.github.io/ Emacs is not for everyone, but it served me well for 25+ years with; ESS is amazing, I often keep many sessions persistently (daemon mode !) for weeks at a time. And then you have Magit and other goodies.
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Replying to @LisaDeBruine
Yep. It tends to become muscle memory, or you learn when you try to commit and the repo is behind :) BTW the higher-end variant is to edit the PS1 variable for your shell to show `git status`. There are a number of tutorials out there that should help given your shell.
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"If you ever see someone using a capital xi in an equation, just observe them quietly to learn as much as you can before they return to their home planet." Beautiful.
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It was twenty years ago today ... ... that I uploaded my first CRAN package. dirk.eddelbuettel.com/blog/2… #rstats
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Rcpp now used by 2500 CRAN packages Seamless R and C++ integration dirk.eddelbuettel.com/blog/2… #rcpp #rstats What a mileston -- a *big big thank you* to the Rcpp Core team, all other contributors, and of course all users!
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"Ability is no longer the only currency in the transfer market. Information, and the skill to interpret it, is just as important now, too." @RorySmith on soccer's talent war for ... data scientists #rstats nytimes.com/2022/02/24/sport…
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Another *truly big moment* for #Rcpp - 2500+ reverse dependencies - Used by one in every 7.6 packages on CRAN So a really *big and heartfelt* Thank You! to everybody who helped along: the Rcpp Core team, all other contributors, and of course all users keeping us at it! #rstats
A *really big moment* for #Rcpp: - 2000 reverse dependecies - One in eight packages on CRAN A *big and heartfelt Thank You!* to everbody who has contributed on that journey with code, suggestions, bug reports, documentation and tips! #rstats
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