Three years ago I wrote a blog post on how to create manhattan plots in R. After hundreds of comments pointing out bugs and other issues, I've finally cleaned up this code and turned it into an R package.The qqman R package is on CRAN: http://cran.r-project.org/... [Read more...]

by Joseph Rickert I recently wrote about some R resources that are available for generalized linear models (GLMs). Looking over the material, I was amazed by the amount of effort that is continuing to go into GLMs, both with with respect to new theoretical developments and also in response to ... [Read more...]

This article serves the purpose of illustrating that signal processing with R is possible – thanks to the signal package – and to keep a reference of some of the stuff that I learned at my last edX course. Anyway, I … Continue reading → [Read more...]

Just received this announcement of the UCLID 2014 conference in Lancaster, July 1-2 2014: Understanding Complex and Large Industrial Data 2014, or UCLID, is a workshop which aims to provide an opportunity for academic researchers and industrial practitioners to work together and share ideas on the fast developing field of ‘big data’ analysis. ... [Read more...]

By Liz Matthews. EARL (Effective Applications of the R Language) is a brand new conference and the first to focus on the growing commercial usage of R.   More and more [Read more...]

In April 2012, I wrote this blog post demonstrating an approach proposed in Lewbel (2012) that identifies endogenous regressor coefficients in a linear triangular system. Now I am happy to announce the release of the ivlewbel package, which contains a function through which Lewbel’s method can be applied in R. This ... [Read more...]

In Part 3 of this series we will explore some more variations to our Sales Dashboard in R and introduce new ways of visualizing sales related data with qplot and ggplot2. If you haven't done it yet, it is recommended to read Part … Continue reading → [Read more...]

In previous posts (here and here) I looked at how generalized additive models (GAMs) can be used to model non-linear trends in time series data. In my previous post I extended the modelling approach to deal with seasonal data where we model both the within year (seasonal) and between year (... [Read more...]

NFL Draft 2014 It can't be easy being a Jacksonville Jaguars fan. It seems that management has learned nothing from the Blaine Gabbert debacle. By that I mean I'm not impressed with their first round pick Blake Bortles. Bucky Brooks of NFL.com called him a “developmental prospect”. Developmental? Is that ... [Read more...]

In our book we provide examples of how to convert IPv4 addresses to integer format (and back). We held ourselves to using only basic R functionality since the book had to be at an introductory level. On a fairly modern box, the ip2long function takes (roughly) 0.1s to convert 4,000 ... [Read more...]

This entry is part 13 of 13 in the series Using RAt Mazama Science we produce web based tools for interrogating important datasets. We are proud to announce the release of a new Population databrowser that allows users to review …   read more ... [Read more...]

A new release of the stringi package is available on CRAN (please wait a few days for Windows and OS X binary builds). stringi is a package providing (but definitely not limiting to) replacements for nearly all the character string…Read more › [Read more...]

If you're in the Philadelphia area and want to hack on some data with other R users this evening, come to the IntegriChain/Revolution Analytics Meetup at Drexel University. There will be an short lecture to introduce the problem, followed by a hacking session (virtual machines with Revolution R software ... [Read more...]

Even though most modern computers already have four cores that can be used to speed up analysis – see here for a description. However, after starting to do more simulation studies it became apparent that this is highly impractical. The solution: Running R via R-studio on Amazons cloud servers. Thanks to ... [Read more...]

In this post, I am about to explain you simple way to find as many best possible regression models you want, from any given predictors dataset. I am going to show you a method, along with code, where you can … Continue reading → [Read more...]

The EMDAT database provides valuable information on human and financial losses from natural disasters around the world. Some of the issues with the EMDAT data are lack of entire data accessibility, static and inconsistent summary reports, and the lack ... [Read more...]

There’s a lot of discussion around why code written by self-taught “scientist programmers” rarely follows what a trained computer scientist would consider “best practice”. Here’s a recent post on the topic. One answer: we begin with exploratory data analysis and never get around to cleaning it up. An ... [Read more...]

The rOpenSci project is a poster child for the fluid collaboration that has become increasingly common these days thanks to platforms like Twitter and GitHub. It has been really inspring to see open discussions take shape as rough ideas, which rapidly turn into prototype research software, all of which are ... [Read more...]

When I set out to build RSiteCatalyst, I had a few major goals: learn R, build a CRAN-worthy package and learn the Adobe Analytics API. As I reflect back on how the package has evolved over the past two years and what I’ve learned, I think my greatest learning ... [Read more...]

By Matt Sundquist Plotly's Co-Founder Here at Plotly, we are on a mission to build a platform where data scientists can analyze data, create beautiful graphs and collaborate: like a GitHub for data, where you can share and find plots, data, and code. The benefits are: Plots (including ggplot2 plots) ... [Read more...]