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Rcpp Workshop in San Francisco Oct 8th
Following the successful one-day master class on Rcpp preceding this year’s R/Finance conference, a full-day master class on Rcpp and related topics which will be held on Saturday, October 8, in San Francisco.
Join Dirk Eddelbuettel for six hours of detailed and hands-on instructions and discussions aroundRcpp, inline, RInside, RcppArmadillo, RcppGSL, RcppEigen 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).
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 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 and RcppEigen for linear algebra (via highly expressive templated C++ libraries) and RcppGSL.
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 the new R ReferenceClasses interact, and how Rcpp sugar lets us write C++ code that is often as expressive as R code. Another possible topic, time permitting, may be writing glue code to extend Rcpp to other C++ projects.
We also expect to leave some time to discuss problems brought by the class participants.
October 8, 2011 – San Franciso
AMA Executive Conference Center
@ the Marriott Hotel
55 4th Street, 2nd Level
San Francisco, CA 94103
|Dirk E has been contributing packages to CRAN for nearly a decade. Among these are RQuantLib, digest, littler, random, RPostgreSQL, as well the Rcpp family of packages comprising Rcpp, RInside, RcppClassic, RcppExamples, RcppDE, RcppArmadillo and RcppEigen. He maintains the CRAN Task Views for Finance as well as High-Performance Computing, and is a founding co-organiser of the annual R / Finance conferences in Chicago. He has Ph.D. in Financial Econometrics from EHESS (Paris), and works in Chicago as a Quantitative Strategist.|
Basically a bar chart shows rectangular bars with length proportional to the quantities being described. It helps to see relative quantities between various category types.
The barplot() command is used for making Bar Plots, while hist() is used for histograms. You can also use the plot() command with type=h to create histograms-The official R manual also suggests that Dot plots using dotchart () are a reasonable substitute for bar plots.
A very simple easy to understand tutorial for basic bar plots is at http://msenux.redwoods.edu/math/R/barplot.php
The difference between the three main functions that can be used for these charts are shown below-
Rural Male Rural Female Urban Male Urban Female
50-54 11.7 8.7 15.4 8.4
55-59 18.1 11.7 24.3 13.6
60-64 26.9 20.3 37.0 19.3
65-69 41.0 30.9 54.6 35.1
70-74 66.0 54.3 71.1 50.0