Publications by Joseph Rickert
Sunbelt XXXV, Social Network Analysis, Statnet and R
by Joseph Rickert The XXXV Sunbelt Conference of the International Network for Social Network Analysis (INSNA) was held last month at Brighton beach in the UK. (And I am still bummed out that I was not there.) A run of 35 conferences is impressive indeed, but the social network analysts have been at it for an even longer time than that: and ...
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Efficient Accumulation in R
by John MountData Scientist, Win-Vector LLC R has a number of very good packages for manipulating and aggregating data (plyr, sqldf, RevoScaleR, data.table, and more), but when it comes to accumulating results the beginning R user is often at sea. The R execution model is a bit exotic so many R users are very uncertain which methods of accumulati...
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MRAN’s Packages Spotlight
by Joseph Rickert New R packages just keep coming. The following plot, constructed with information from the monthly files on Dirk Eddelbuettel's CRANberries site, shows a plot of the number of new packages released to CRAN between January 1, 2013 and July 27, 2015 by month (not quite 31 months). This is amazing growth! The mean rate is about ...
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A Short Introduction to Bioconductor
by Peter Hickey (@PeteHaitch) One of the keys to R's success as a software environment for data analysis is the availability of user-contributed packages. Most useRs will be familiar with (and very grateful for) the Comprehensive R Archive Network (CRAN). The packages available on CRAN, nearly 7000 at last count, cover common data analysis tasks,...
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A simple statnet model of CRAN
by Joseph Rickert In a recent post on creating JavaScript network graphs directly from R, my colleague and fellow blogger, Andrie de Vries, included a link to a saved graph of CRAN. Here, I will use that same graph (network) to build a simple exponential random graph model using functions from the igraph package, and the network and ergm pac...
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How do you know if your data has signal?
by Nina ZumelData Scientist Win-Vector LLC Image by Liz Sullivan, Creative Commons. Source: Wikimedia An all too common approach to modeling in data science is to throw all possible variables at a modeling procedure and “let the algorithm sort it out.” This is tempting when you are not sure what are the true causes or predictors of the pheno...
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R News From JSM 2015
by Joseph Rickert We can declare 2015 the year that R went mainstream at the JSM. There is no doubt about it, the calculations, visualizations and deep thinking of a great many of the world's statisticians are rendered or expressed in R and the JSM is with the program. In 2013 I was happy to have stumbled into a talk where an FDA statistici...
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Using Azure as an R datasource, Part 4 – Pulling data from SQL Server to Linux
by Gregory VandenbrouckSoftware Engineer, Microsoft This post is the fourth in a series that covers pulling data from Microsoft SQL Server or MySQL/MariaDB on Azure to an R client on Windows or Linux. In the previous posts, we covered pulling data from SQL Server to Windows and from MySQL/MariaDB to both Windows and Linux. This time we’ll be p...
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5 New R Packages for Data Scientists
by Joseph Rickert One great beauty of the R ecosystem, and perhaps the primary reason for R’s phenomenal growth, is the system for contributing new packages. This, coupled to the rock solid stability of CRAN, R’s primary package repository, gives R a great advantage. However, anyone with enough technical knowhow to formulate a proper submis...
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Following up on news stories with choroplethr and R
by Ari Lamstein, consultant specializing in software engineering and data analysis and author of the free email course Learn to Map Census Data in R. One of my favorite things about R is that it allows me to follow up on interesting news stories. Consider this interview on EconTalk about the history of fracking in America. Russ Roberts interview...
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