Posts Tagged ‘ packages ’

Two new rOpenSci R packages are on CRAN

October 27, 2011
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Two new rOpenSci R packages are on CRAN

Carl Boettiger, a graduate student at UC Davis, just got two packages on CRAN.  One is treebase, which which handshakes with the Treebase API.  The other is rfishbase, which connects with the Fishbase, although I believe just scrapes XML cont...

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Mixed-Effects Models in R with Quantum Forest

October 26, 2011
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For anyone who wants to estimate linear or nonlinear mixed-effects models (aka random-effects models, hierarchical models or multilevel models) using the R language, the Quantum Forest blog has several recent posts that will be of interest. Written by Luis Apiolaza from the School of Forestry at the University of Canterbury in New Zealand, the blog includes a number of...

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ggplot2 for big data

October 21, 2011
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ggplot2 for big data

(Hadley Wickham, author of ggplot2 and several other R packages, guest blogs today about forthcoming big-data improvements to his R graphics package -- ed.) Hi! I'm Hadley Wickham and I'm guest posting on the Revolutions blog to give you a taste of some of the visualisation work that my research team and I worked on this summer. This work...

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Speed up recursion in R 600-fold with Rcpp

September 12, 2011
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Rcpp package co-author Dirk Eddelbuettel provides another case study in speeding up R code by rewriting repeatedly-called R code as inline C++ functions, using the classic Fibonacci recursion algorithm as an example. The speed gains here are impressive -- over 600x compared to native recursive R code -- but you could also improve performance by using a more efficient,...

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The problem with R? Too much new stuff!

August 23, 2011
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In a tongue-in-cheek post at the Information Management blog, Steve Miller shares his "frustration" with R: package developers keep on releasing new functionality for R that makes his own work obsolete. For example, there's now pre-packaged functionality in R for enhanced dotplots, Economist-style graphics, additive regression models and more, which all obviate the need for Steve to implement such...

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useR! 2011 roundup

August 19, 2011
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useR! 2011 roundup

As I stand here at Heathrow waiting for my flight back to the States, I thought I'd dash off a few quick reflections of the userR! 2011 conference at University Warwick. It was an outstanding event. There's something about a conference of just a few hundred attendees (there were about 450) that creates a sense of camaraderie and common...

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Model Validation: Interpreting Residual Plots

July 18, 2011
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Model Validation: Interpreting Residual Plots

When conducting any statistical analysis it is important to evaluate how well the model fits the data and that the data meet the assumptions of the model. There are numerous ways to do this and a variety of statistical tests to evaluate deviations from model assumptions. However, there is little general acceptance of any of the statistical tests. Generally...

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Using R and Motion Charts to analyze financial data

July 15, 2011
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Using R and Motion Charts to analyze financial data

We've noted before that with the RGoogleVis package, it's easy to make motion charts in R, and create a web-based interactive chart that reflects the synchronous movements of two or three variables over time. R user Jeffrey Breen has a great new blog post showing exactly how easy it is, which is best summarized in this tweet: I wanted...

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The R Journal: June 2011

June 24, 2011
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The latest issue of the R Journal is out, and as always includes many useful articles about using R and R packages. Articles in Volume 3/1 dive into topics including creating test for R packages with test_that; dealing with times, time zones, dates and holidays with timeDate; social network analysis of mailing lists through text mining; creating choropleths and...

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Speed up R "for" loops 50x with Rcpp

June 23, 2011
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Christian Gunning has a great example of using Rcpp to speed up a for loop in R. For his agent-based simulation, Christian needed to repeatedly call the rbinom function in a loop. (Unfortunately, you can't pass a vector to the size argument, which would have solved the problem.) Using the aaply function (from the plyr package) took about 38...

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