The 10th Kölner R user meeting took place last Friday at the Institute of Sociology and to celebrate the anniversary we invited Andrie de Vries to join us from Revolution Analytics. Andrie is well known in the R community; he is the co-author of the R for Dummies book ... [Read more...]

for over two decades now, researchers at cms have produced the definitive complex sample survey dataset of americans covered by medicare: the medicare current beneficiary survey (mcbs).  i bristle with righteous indignation when healthcare researc... [Read more...]

The R function capture.output() can be used to “collect” the output of functions such as cat() and print() to strings. For example,

> s <- capture.output({<br>+     cat("Hello\nworld!\n")<br>+     print(pi)<br>+ })<br>> s<br>[1] "Hello"        "world!"       "[1] 3.141593"<br>

More precisely, it captures all output sent to the standard output and returns a character vector where each element correspond to a line of output. By ... [Read more...]

At the recent R/Finance 2014 conference in Chicago I gave a talk on Smooth Transition AR models and a new package for estimating them called twinkle. In this blog post I will provide a short outline of the models and an introduction to the package and its features. Financial markets ... [Read more...]

I live (and work!) near one of the most beautiful vantage points for sunsets in possibly the entire US. However almost every beautiful sunset I have seen from there has come from either 1) me walking out of work and … Continue reading → [Read more...]

Unless you’ve been living under a rock for the last few years, you have probably heard of TV shows such as Breaking Bad, Mad Men, How I Met Your Mother or Game of Thrones. While I generally don’t spend a whole lot of time watching TV, I have ... [Read more...]

I recently came across a short tutorial by Peter Norvig on natural language processing using some interesting examples. I found it very interesting and really liked Peter Norvig’s explanations and the fact that it was all in ipython notebook for … Continue reading → [Read more...]

(By Achim Zeileis) After 36 years the FIFA World Cup returns to South America with the 2014 event being hosted in Brazil (after 1978 in Argentina). And as in all previous [Read more...]

A sequence of 9 courses on Data Science will start on Coursera on 2 June and 7 July 2014, to be lectured by(Associate/Assistant) Professors of Johns Hopkins University. The courses are designed for students to learn to become Data Scientists … Continue reading → [Read more...]

Rainfall estimates at desired frequency (e.g., 1% annual chance or 100-year return period) and duration (e.g., 24-hour) are often required in the design of dams and other hydraulic structures, catastrophe risk modeling, environmental planning and manag... [Read more...]

Since this is the first post on this blog, a quick start up for those who may be reading this … Continue reading → [Read more...]

The most popular accounts on twitter have millions of followers, but what are their demographics like? Twitter doesn’t collect or release this kind of information, and even things like name and location are only voluntarily added to people’s profiles. Unlike Google+ … Continue reading → [Read more...]

I am a listener to BBC's podcast More or Less. In the program Tim Harford looks at data with both humour and determination to find what the numbers mean. Last week he handled a listener question. Does everybody get a significant birthday (20, 30 years ... [Read more...]

In our day to day life, we come across a large number of Recommendation engines like Facebook Recommendation Engine for Friends’ suggestions, and suggestions of similar Like Pages, Youtube recommendation engine suggesting videos similar to our previous searches/preferences. In today’s blog post I will explain how to build ... [Read more...]

This gist from @hadley has been on my mind for some time. This was already a follow up of this post from @johnmyleswhite. The problem was that sugar vectorised code suffered a performance penalty compared to devectorised code. This is particularly troubling me because the whole point of sugar is ... [Read more...]

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A picture suitable for a fancy pipe enthusiast My good friend Andrew recently posted this gist: It shows how to solve a simple programming exercise know as FizzBuzz in R, but also is clearly showing off his already amazing proficiency in the very new R package magrittr. Those are some ... [Read more...]

And now for something completely difference, the reduce function, doing something similar to what the Reduce function does in R: #include using namespace Rcpp ; // [[Rcpp::export]] double reduce_example(NumericVector x ){ auto ad... [Read more...]

@kevinushey requested some functional programming in Rcpp11 and provided initial versions of map and filter. map is actually doing exactly the same thing as mapply so I added map as a synonym to mapply so that we can do (see this previous post for details):

// [[Rcpp::export]]
NumericVector mapply_example(NumericVector x, NumericVector y, double z){

    auto fun = [](double a, double b, double c){ return a + b + c ;} ;
    return map( fun, x, y, z ) ;

}

filter takes a sugar ... [Read more...]

I’m still hopeful of working up the idea of recreational data as a popular pastime activity with a regular column somewhere and a stocking filler book each Christmas (?!;-), but haven’t had much time to commit to working up some great examples lately:-( However, here’s a ... [Read more...]