Blog Archives

R-users.com: invite fellow R-users to Jobs, conferences, and R-projects

March 6, 2014
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R-users.com: invite fellow R-users to Jobs, conferences, and R-projects

Dear R users, I am happy to officially announce a new website called R-users.com. The idea of the site is that community members will invite other R users to join them in their R projects, conferences, and work places. This site is a “job board” for R users, hosting various “call to action” to R-users,

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Plotly Beta: Collaborative Plotting with R

December 16, 2013
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Plotly Beta: Collaborative Plotting with R

(Guest post by Matt Sundquist on a lovely new service which is pro-actively supporting an API for R) The Plotly R graphing library  allows you to create and share interactive, publication-quality plots in your browser. Plotly is also built for …Read more »

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R-bloggers: an example of how interest networks propel viral events

December 4, 2013
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R-bloggers: an example of how interest networks propel viral events

A guest post by Jeff Hemsley, who has co-authored with Karine Nahon a new book titled Going Viral. ————————- In Going Viral (Polity Press, 2013) we explore the topic of virality, the process of sharing messages that results in a fast, broad …Read more »

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R 3.0.2 and RStudio 0.9.8 are released!

September 26, 2013
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R 3.0.2 (codename “Frisbee Sailing”) was released yesterday. The full list of new features and bug fixes is provided below. Also, RStudio v0.98 (in a “secret” preview) was announced two days ago with MANY new features, including: Amazing new debugging …Read more »

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A speed test comparison of plyr, data.table, and dplyr

September 23, 2013
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A speed test comparison of plyr, data.table, and dplyr

Guest post by Jake Russ For a recent project I needed to make a simple sum calculation on a rather large data frame (0.8 GB, 4+ million rows, and ~80,000 groups). As an avid user of Hadley Wickham’s packages, my first …Read more »

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K-means Clustering (from “R in Action”)

August 7, 2013
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K-means Clustering (from “R in Action”)

In R’s partitioning approach, observations are divided into K groups and reshuffled to form the most cohesive clusters possible according to a given criterion. There are two methods—K-means and partitioning around mediods (PAM). In this article, based on chapter 16 of R in Action, Second Edition, author Rob Kabacoff discusses K-means clustering. Read more »

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Analyzing Your Data on the AWS Cloud (with R)

July 22, 2013
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Analyzing Your Data on the AWS Cloud (with R)

Guest post by Jonathan Rosenblatt Disclaimer: This post is not intended to be a comprehensive review, but more of a “getting started guide”. If I did not mention an important tool or package I apologize, and invite readers to contribute in the comments. …Read more »

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Tailor Your Tables with stargazer: New Features for LaTeX and Text Output

July 15, 2013
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Tailor Your Tables with stargazer: New Features for LaTeX and Text Output

Guest post by Marek Hlavac Since its first introduction on this blog, stargazer, a package for turning R statistical output into beautiful LaTeX and ASCII text tables, has made a great deal of progress. Compared to available alternatives (such as …Read more »

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Creating good looking survival curves – the ‘ggsurv’ function

July 4, 2013
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Creating good looking survival curves – the ‘ggsurv’ function

This is a guest post by Edwin Thoen Currently I am doing my master thesis on multi-state models. Survival analysis was my favourite course in the masters program, partly because of the great survival package which is maintained by Terry Therneau. The …Read more »

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Top 100 R packages for 2013 (Jan-May)!

June 13, 2013
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Top 100 R packages for 2013 (Jan-May)!

(This article was first published on R-statistics blog » RR-statistics blog, and kindly contributed to R-bloggers) What are the top 100 (most downloaded) R packages in 2013? Thanks to the recent release of RStudio of their “0-cloud” CRAN log files (but without including downloads from the primary CRAN mirror or any of the 88 other CRAN mirrors), we can now answer this question...

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