The Cauchy distribution (?dcauchy in R) nails a flashlight over the number line and swings it at a constant speed from 9 o’clock down to 6 o’clock over to 3 o’clock. (Or the other direction, from 3→6→9.) Then counts Read more »

The Cauchy distribution (?dcauchy in R) nails a flashlight over the number line and swings it at a constant speed from 9 o’clock down to 6 o’clock over to 3 o’clock. (Or the other direction, from 3→6→9.) Then counts Read more »

When I want to insert figures generated in R into a LaTeX document, it looks better if I first remove the white space around the figure. Unfortunately, R does not make this easy as the graphs are generated to look good on a screen, not in a document. There are two things that can be done to fix this...

Another number theory puzzle, completed in the plane to Hamburg: Integers n are called noble if they can be decomposed as a sum n=a+b+… of distinct integers such that 1/a+1/b+…=1. They are called bourgeois if they are not noble but can be decomposed as a sum n=a+b+… of integers, some of them identical, such that

Now, after reading in data, making plots and organising commands with scripts and Sweave, we’re ready to do some numerical data analysis. If you’re following this introduction, you’ve probably been waiting for this moment, but I really think it’s a good idea to start with graphics and scripting before statistical calculations. We’ll use the silly

How to control the limits of data values in R plots. R has multiple graphics engines. Here we will talk about the base graphics and the ggplot2 package. We’ll create a bit of data to use in the examples: one2ten <- 1:10 ggplot2 demands that you have a data frame: ggdat <- data.frame(first=one2ten, second=one2ten) Seriously The post Plot...

(This article was first published on Rmetrics blogs, and kindly contributed to R-bloggers) To leave a comment for the author, please follow the link and comment on their blog: Rmetrics blogs. R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave,...

As of the beginning of 2013, Data Community DC ran three Meetup groups: Data Science DC, Data Business DC, and R Users DC. We’ve often wondered how much these three groups overlapped. In this post, I’m going to show you … Continue reading → The post Examining Overlapping Meetup Memberships with Venn Diagrams appeared first on Data...

A new Armadillo version 3.6.3 came out this morning, and the corresponding RcppArmadillo version is now on CRAN. Changes are incremental: Changes in RcppArmadillo version 0.3.6.3 (2013-02-20) Upgraded to Armadillo release Version 3.6.3 ...

At D-RUG this week Rosemary Hartman presented a really useful case study in model selection, based on her work on frog habitat. Here is her code run through ‘knitr’. Original code and data are posted here. (yes, I am just doing this for the flying monkey) Editor’s note: we’re giving away flying monkey dolls from our...

This guest post is by Tammer Kamel, Founder of Quandl Finding and formatting numerical data for analysis in R or Excel or indeed any application is a pain that all real world data analysts know all too well. In aggregate I have probably spent weeks of my life trying to find data on the web. And several more weeks...

GitHub recently launched a more powerful search feature which has been used on more than one occasion to identify sensitive files that may be hosted in a public GitHub repository. When used innocently, there are all sorts of fun things you can find with this search feature. Inspired by Aldo Cortesi's post documenting his exploration

Last summer, I had some internet connectivity problems. Specifically, I would have massive latency issues that affected my conversations on Skype and my relatively pathetic under the best of circumstances efforts at online gaming. It was driving me up a wall and I couldn't figure it out. It hadn't...

This is an example of interfacing R, shiny, and deSolve to produce an interactive environment where users can explore model behavior by altering parameters in an easy to use GUI. The model tracks the number of susceptible, infectious, and recovered individuals in two co-occuring host species. The rates of change for each class are represented as a system of differential...

A decent percentage of working time in R, I spend looping over chromosomes, transcription factors or tissues, usually, using parallelization.To get the stuff to run simultaneously I use the foreach function from the doMC package, and for monitoring of ...

This is an example of interfacing R, shiny, and deSolve to produce an interactive environment where users can explore model behavior by altering parameters in an easy to use GUI. The model tracks the number of susceptible, infectious, and recovered individuals in two co-occuring host species. The rates of change for each class are represented as a system of...

The past few posts on momentum with R focused on a relatively simple way to backtest momentum strategies. In part 4, I use the quantstrat framework to backtest a momentum strategy. Using quantstrat opens the door to several features and options as well as an order book to check the trades at the completion of … Continue reading...

Since at some point I had trouble with a conflict between knitr and the latex package textpos, I used the lesser Sweave in Another Experiment with R and Sweave. I ran the Sweave2knitr command and discovered that textpos and knitr play well togeth...

Anyone interested in playing around with the data generated by the PITCHf/x cameras at major league baseball games should definitely check out the pitchRx package from Carson Sievert. Major League Baseball Advanced Media makes the data available for download, and this package provides an interface from R to the speed, position and pitcher data for just about every MLB...