I knew R was versatile, but DANG, people do a lot with it: > > … I don’t think anyone actually believes that R is designed to make *everyone* happy. For me, R does about 99% of the things I … Continue reading →

One of Rs great strengths compared to other statistic solutions or programming languages is the amount of possibilities for creating well-designed publication-quality plots. Almost all plot types can be created with any amount of fine tuning. R works on small data sets as well as on big data. In addition to Rs base-graphics various add-on

Arguably, knitr (CRAN link) is the most outstanding R package of this year and its creator, Yihui Xie is the star of the useR! conference 2012. This is because the ease of use comparing to Sweave for making reproducible report. Integration of knitR and R Studio has made reproducible research much more convenience, intuitive and easier to

Where do these come from? Since most statistical packages calculate these estimates automatically, it is not unreasonable to think that many researchers using applied econometrics are unfamiliar with the exact details of their computation. For the purposes of illustration, I am going to estimate different standard errors from a basic linear regression model: , using the

Hi, our group of R users from INSEE, aka FLR, meets monthly in Paris. Next meeting is on Wed 13 (tomorrow), 1-2 pm, room 539 (an ID is needed to come in, map to access INSEE R), about ggplot2 and parallel computing. Since the first meeting in February, presentations have included hot topics like webscrapping, C in R, RStudio, SQLite

Once again working on my slides for the AMSI Lecture 2012 tour, it took me a while to get the following LaTeX code (about the family reunion puzzle) to work: \begin{frame} \slidetitle{A family meeting} \begin{block}{Random switch of couples} \only<1>{ \begin{itemize} \item Pick two couples at random with probabilities proportional to the

Recommender systems are pervasive. You have encountered them while buying a book on barnesandnoble, renting a movie on Netflix, listening to music on Pandora, to finding the bar visit (FourSquare). Saar for Revolution Analytics, had demonstrated how to get started with some techniques for R here. We will build some using Michael Hahsler’s excellent package

I fought with my LαTεX compiler this morning as it did not want to deal with my code: looking on forums for incompatibilities between beamer and algorithmic, and adding all kinds of packages, to no avail. Until I realised one \STATE was missing: (This is connected with my AMSI public lecture on simulation, obviously!) Filed