- Writing functions is an important part of programming, and in order to write proper functions you need to know how to debug when your functions aren’t working. Slawa Rokicki, PhD student at Harvard, explains How to write and debug an R function.
- It is often said that you should avoid loops in R because R is extremely slow with iterations, and hence many R-programmers try to avoid loops by working with matrices and arrays. Did you know that an even better option is to run your loops in C++ and import your result back into R? Here is a quick tutorial called how you can use C++ within R.
- Rasmus Bååth blogs about the The Most Comprehensive Review of Comic Books Teaching Statistics.
- Did you know that more and more startups are starting to use R as their primary data analysis tool? According to Revolution Analytics, Uber and CultureAmp have just joined the R camp.
- Xi’an reviews a new paper called Generalizations related to hypothesis testing with the Posterior distribution of the Likelihood Ratio by Smith and Ferrari.
- And finally, DiffusePrioR writes “If history can tell us anything about the World Cup, it’s that the host nation has an advantage of all other teams”. Do you agree or disagree, and what do you think is Brazil’s chance of winning the World Cup?
- Like the plots above? Learn how to create these in R from Freakonometrics’ new post called Box plot, Fisher’s style.
- If you are on the job market, Tal Galili from R bloggers has compiled 6 new R jobs for seekers like you.
- Big Data has gained lots of popularity recently, and every data scientist should know at least something about it. If you are new to data science, consider this introduction to R for Big Data with PivotalR.
- Using Repeated Measures to Remove Artifacts from Longitudinal Data by Dmitry Grapov.
- And finally, Andrew Gelman discusses Why we hate stepwise regression.
Right now I’m working on a project that involves new ways to view units of content and the relationships between them. I’ve posted the comic I worked on, it has a number of stats references throughout. This is early alpha stages for the software, you may run into issues. To see the relationships, go to the puffball menu and make sure that “Show relationships” is clicked.
- Alvaro Galindo reviews Social Media Mining with R by by Nathan Danneman and Richard Heinmann.
- Some popular articles on R tip and tricks are: R has some sharp corners by Win-Vector LLC, Sample uniformly within a fixed radius by Forester (Assistant Professor at the University of Minnesota Twin Cities), The Birthday Simulation by Wes Stevenson, and didYouMean() Function: Using Google to correct errors in Strings by Sam Weiss.
- R bloggers compiles a list of R related positions for those who are on the job market.
- Xi’an discusses a special issue Statistical Science named Big Bayes Stories: A Collection of Vignettes.
- Last week, we featured an article on R vs. Julia. This week, Matloff (aka Mad (Data) Scientist) writes another comparison called R beats Python! R beats Julia! Anyone else wanna challenge R?
- Are you a self-taught “scientist programmer”? Here is why people think code written by people like you is ugly.
- As always, R articles are extremely popular. This week, we have: Facebook teaches you exploratory data analysis with R by Revolution Analytics, Beyond R, or on the Hunt for New Tools by Quintuitive, Bootstrap Critisim (with example) by Eran Raviv, The apply command 101 by Learning R by Imitation, and Can We do Better than R-squared? by Learning as You Go.
- Julia is a new programming language (only 2 years old) for scientific computing and it has gained lots of popularity recently. In the past, we shared some articles comparing R and Julia. This week, Alvaro Galindo writes another comparison called Julia versus R – Playing around.
- Sébastien Bubeck, assistant professor at Princeton, releases the first draft of his monograph based some old lecture notes called Theory of Convex Optimization for Machine Learning.
- And finally, happy Victoria Day to those in Canada!