Having posted some code to Git a few days ago and having been wholly dissatisfied with it, I began to do what I often do with code I don’t like. I started re-writing it bigger and weirder and more philosophically pure. Part of this search for Platonic code lead me to explore object oriented programming 
In this article we’ll get up and running on the Semantic Web in less than 5 minutes using SPARQL with R. We’ll begin with a brief introduction to the Semantic Web then cover some simple steps for downloading and analyzing government data via a SPARQL query with the SPARQL R package. What is the Semantic
The post SPARQL...
In case you missed them, here are some articles from December of particular interest to R users. The blog is.R ran an excellent series of R tips and applications in December, with posts including working with Stata files, working with graphs and networks, and text analysis. Kohske Takahashi provides R scripts to create a collection of optical illusions. Highlights...
Restricted Boltzmann Machines (RBMs) are an unsupervised learning method (like principal components). An RBM is a probabilistic and undirected graphical model. They are becoming more popular in machine learning due to recent success in training them with contrastive divergence. They have been proven useful in collaborative filtering, being one of the most successful methods...
I really enjoyed tonight’s DC R Meetup, presented by the prolific Anthony Damico. I’ve met Anthony before to discuss whether the Census Bureau could either… publish R-readable … Continue reading →
One of the many things I keep avoiding is statistics. I’ve never really been convinced about the 5% significance level thing; as far as I can tell, hardly anything that’s interesting normally distributes; all the counting that’s involved just confuses me; and I never really got to grips with confidently combining probabilities. I find a 
As mentioned in the Appendix of Modern Actuarial Risk Theory, “R (and S) is the ‘lingua franca’ of data analysis and statistical computing, used in academia, climate research, computer science, bioinformatics, pharmaceutical industry, customer analytics, data mining, finance and by some insurers. Apart from being stable, fast, always up-to-date and very versatile, the chief advantage of R is that...
This a brief guide to using R in collaborative, social ways. R is a powerful open-source programming language for data analysis, statistics, and visualization, but much of its power derives from a large, engaged community of users. This is an introduction to tools for engaging the community to improve your R code and collaborate with others.
(Am I...
the meps household component leads the pack for examining individual-level medical expenditures by payor and type of service. total expenditures captured by the survey tend to be low, but unbiased across the board and can be adjusted to match the...
Gaston Sanchez has just published an online pdf of his new book PLS Path Modeling with R.I have been using Gaston's plspm r package for a couple of years to analyze marketing data. I started when I needed to test a path model in wh...
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
