New York Open Statistical Programming Meetup Message Board › Rcpp Master Class with Dirk Eddelbuettel
New York, NY
Great seeing many of you last night at Sean Taylor’s talk. And a big thanks to Pivotal Labs again for hosting us. I hope everyone is looking forward to seeing Bryan Lewis in a couple weeks.
As I mentioned last night, I am helping organize a day-long Rcpp master class taught by Dirk Eddelbuettel (author of Rcpp and coorganizer of the R in Finance conference) on Saturday, March 9th. It is an intensive six hours of personal instruction from Dirk focusing on writing C++ code for R consumption, building packages with C++ code, using RcppArmadillo for linear algebra, RInside and other high performance computing issues.
It is meant to be an intimate course so it is capped at 30 participants. To make the class accessible the price is being kept low at $500 which is significantly less than is usually charged for these types of courses. Some of the proceeds will be donated back to this meetup to help fund future meetups.
You can sign up and pay here: http://www.meetup.com...
If using Paypal is a problem contact me and we will find an alternative form of payment.
Please feel free to email me with any questions.
Below is a description of the class. I hope it will be of interest to many of you in this group.
Join Dirk Eddelbuettel for six hours of detailed and hands-on instructions and discussions around Rcpp, RInside, RcppArmadillo, RcppGSL and other packages---in an intimate small-group setting.
The full-day format allows combining an introductory morning session with a more advanced afternoon session while leaving room for sufficient breaks. We plan on having about six hours of instructions, a one-hour lunch break and two half-hour coffee breaks (and lunch and refreshments will be provided).
Rcpp has become the most widely-used language extension for R. Currently deployed by 103 CRAN packages and a further 10 BioConductor packages, it permits users and developers to pass "whole R objects" with ease between R and C++, bringing the depth of the R analysis framework together with C++ for anything ranging from higher-performance computations (particularly simulations) to connections to other frameworks and libraries written in C or C++ --- a 'no compromise' link between R and C++.
Morning session: "A Hands-on Introduction to R and C++"
The morning session will provide a practical introduction to the Rcpp package (and other related packages). The focus will be on simple and straightforward applications of Rcpp in order to extend R and/or to significantly accelerate the execution of simple functions. The tutorial will cover Rcpp attributes as well as the inline package which permits embedding of self-contained C, C++ or FORTRAN code in R scripts. We will also discuss RInside, to easily embed the R engine code in C++ applications, as well as standard Rcpp extension packages such as RcppArmadillo for linear algebra (via highly expressive templated C++ libraries).
Afternoon session: "Advanced R and C++ Topics"
The afternoon tutorial will provide a hands-on introduction to more advanced Rcpp features. It will cover topics such as writing packages that use Rcpp, how Rcpp modules and R ReferenceClasses interact, how Rcpp sugar lets us write C++ code that is often as expressive as R code, and how Rcpp attributes allow for the easiest integration yet of R and C++. Another possible topic, time permitting, may be writing glue code to extend Rcpp to other C++ projects as a concrete study.
We also expect to leave some time to discuss problems brought by the class participants.
Dirk Eddelbuettel has been writing R / CRAN packages for over a decade, currently maintains 20, including Rcpp and several related packages, and contributes to a few others. He maintains the CRAN Task Views for Finance as well as High-Performance Computing, is a founding co-organiser of the annual R / Finance conference in Chicago, and an editor of the Journal of Statistical Software. He has Ph.D. in Financial Econometrics from EHESS (Paris), and works in Chicago as a Senior Quantitative Analyst.