Monthly Archives: September 2013

Profiling R code

September 25, 2013
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Profiling R code

Profiling R code gives you the chance to identify bottlenecks and pieces of code that needs to be more efficiently implemented . Profiling R code is usually the last thing I do in the process of package (or function) development. In my experience we can reduce the amount of time necessary to run an R

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R as a command-line tool for data science

September 24, 2013
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Data Scientist Jeroen Janssens recently published a useful list of 7 data science tools that you can use from the command line. This doesn't just mean they're convenient tools for command-line junkies: it also means you can easily chain them together with data sources for offline, automated processes. Included in the list are JSON processing tools (jq, json2csv), the...

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Patterns in the Ivy II: Beyond the Giant Component

September 24, 2013
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Patterns in the Ivy II: Beyond the Giant Component

Last week’s post on the metal collaboration network brought attention largely to the “giant component”–the largest subgraph in a network where all actors have at least one path to all other actors. In large networks, even sparse ones, giant components typically emerge and include the majority of actors in the network. While focusing on the… Continue reading →

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You stole my idea!

September 24, 2013
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You stole my idea!

Earlier today, Gareth has showed me a recent, interesting paper by Michael Sweeting (and colleagues). In the paper, Micheal et al describe their work on a R package to extend on the framework of the Continual Reassessment Method (the ori...

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My talk @ GSK

September 24, 2013
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This Thursday I'll give a talk at the GSK Statistics Forum. Erika (with whom I shared a train journey to the 2012 BayesPharma and a group walk in Oxfordshire a few years back) now works at GSK and invited me. I will talk about the model for c...

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RStudio v0.98 Preview (Debugging Tools and More)

September 24, 2013
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RStudio v0.98 Preview (Debugging Tools and More)

We’re very pleased to announce that a preview release of RStudio IDE v0.98 is available for download now. Major highlights of the new release include debugging tools, many improvements to environment/workspace browsing, and a new way to create HTML5 presentations using R Markdown. As usual there are also many small improvements and bug fixes. We’ll

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Bio7 1.7.1 for Linux Released

September 24, 2013
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Bio7 1.7.1 for Linux Released

24.09.2013 I released a new Linux version of Bio7 (64-bit only – see Screenshots below). For an overview of the new features please read the release notes for Windows 1.7.0 and 1.7.1: http://bio7.org/?p=2049 http://bio7.org/?p=2112 In addition some Linux specific improvements are embedded in this release. Additional Linux features: Rserve can be opened with a Gnome

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Zurich, Oct 2013 – R Crash Course

September 24, 2013
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(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 his blog: Rmetrics blogs. R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web...

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Working with intraday data

September 24, 2013
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When working with intraday data, analysts are often facing a large dataset problem. R is well equipped to deal with this but the standard approach has to be modified in some ways. Large dataset means different things to different people. I’m talking here about a dataset of less than 10 columns and 2 to 5

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Munkres’ Assignment Algorithm with RcppArmadillo

September 24, 2013
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Munkres’ Assignment Algorithm with RcppArmadillo

Munkres’ Assignment Algorithm (Munkres (1957), also known as hungarian algorithm) is a well known algorithm in Operations Research solving the problem to optimally assign N jobs to N workers. I needed to solve the Minimal Assignment Problem for a relabeling algorithm in MCMC sampling for finite mixture distributions, where I use a random permutation Gibbs sampler. For each sample...

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