Do not resort to Monte Carlo methods unnecessarily. When I received this 2009 Springer-Verlag book, Computational Statistics, by James Gentle a while ago, I briefly took a look at the table of contents and decided to have a better look later… Now that I have gone through the whole book, I ...

Lately I’ve been writing maximum likelihood estimation code by hand for some economic models that I’m working with. It’s actually a fairly simple task, so I thought that I would write up the basic approach in case there are readers who haven’t built a generic estimation ...

Networks – social and biological – are all the rage, just now. Indeed, a recent entry at Duncan’s QOTD described the “hairball” network representation as the dominant cultural icon in molecular biology. I’ve not had occasion to explore networks “professionally”, but have always been fascinated by both networks and the ...

Here’s the situation. Web applications, built using a framework (e.g. Rails, Django) are great for fetching data from a database and rendering it. They’re not so great for crunching and charting the data. Conversely, R is great for crunching and charting, but doesn’t make for a ...

After reading (most of) “The Scientists and Engineers Guide to Digital Signal Processing” by Steven W. Smith, PhD, I decided to take a second crack at the ECG data. I wrote a set of R functions that implement a windowed (Blackman) sinc low-pass filter. The convolution of filter kernel with ...

This post presents an experience I had optimising the efficiency of code for a data analysis task in R. I'm not an expert in programming nor code optimisation. However, I thought my experience might make an interesting case study for others at a simila...

For more than ten years, I have been teaching R both formally and informally. One thing that I find often trips up students is the use of R’s accessors and mutators. ( For those readers not from a formal computer science background, an accessor is a method for accessing data ...