The best part about writing a dissertation is finding clever ways to procrastinate. The motivation for this blog comes from one of the more creative ways I’ve found to keep myself from writing. I’ve posted about data mining in the past and this post follows up on those ideas using a topic that is relevant 
(This article was first published on Quantifying Memory, and kindly contributed to R-bloggers) In this post I show how to select relevant bits of the GDELT data in R and present some introductory ideas about how to visualise it as a network map. I've included all the code used to generate the illustrations. Because of this, if you here...
I am continuing in Sync: How Order Emerges from Chaos in the Universe, Nature, and Daily Lifeby Steven Strogatz. To get a feeling on it, I was building a group of things which have only a minute influence on each other are able to synchronize thei...
In case you missed them, here are some articles from March of particular interest to R users. Facebook used R to analyze profile photo changes to create a map of same-sex marriage support in the USA. Joe Rickert contrasts random sampling with fitting models directly to large data sets. A presentation by Carlos Somohano summarizes the history, skills and...
My friend Jonah asked me to guest lecture in his R seminar aimed at grad students and postdocs in Integrative Biology. I gave Jonah a bunch of topics ranging from reproducible research with R to data manipulation. The consensus was data visualization so I put together a 2 hour talk/hands on presentation for ggplot2 beginners.
R is a piece of software, but it is also a community. Help community The most visible aspect of the R community is help. This is also the most useful to new users. The initial sense of cooperation with R was driven mainly by people helping each other. You don’t need to actively participate in
The post R...
Rodrigo Zamith's NCAA Tournament Visualizer is a great example of an interactive data visualization. If you want to create something similar, Rodrigo has shared detailed behind-the-scenes information on how it was created. He used a mix of tools: Python was used to scrape team statistics fromt the NCAA website R was used to prepare the data for analysis, and...
I wrote already about changing figure options mid-chunk in reproducible research. This can be important e.g. if you are looping through a dataset to produce a graphic for each variable but the figure width or height need to depend on properties of the variables, e.g. if you are producing histograms and want the figures to
Last week I ran an introductory workshop on the analysis and visualisation of spatial data with R. The software has become established as one of the best around for statistics and it is becoming increasingly recognised as a tool for data visualisation (I wrote about this last year, also see here) and spatial analysis. Interest in R ...
The Dirichlet process provides a very interesting approach to understand group assignments and models for clustering effects. Often time we encounter the k-means approach. However, it is necessary to have a fixed number of clusters. Often we encounter situations where we don’t know how many fixed clusters we need. Suppose we’re trying to identify
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
