There is a nice R module for apache: rApache. So you can easily publish statistics.

There is a nice R module for apache: rApache. So you can easily publish statistics.

If your WordPress blog is hosted at WordPress.com (like this one), you may know that source code in posts is formatted and highlighted using a shortcode, as explained here. Until recently, R was not on the list of supported languages (neither was Perl), but I noticed today that both of them are now supported. This

What’s a “Friday fun project”? It’s a small computing project, perfect for a Friday afternoon, which serves the dual purpose of (1) keeping your programming/data analysis skills sharp and (2) providing a mental break from the grind of your day job. Ideally, the skills learned on the project are useful and transferable to your work

In my previous post, I motivated a web application that would allow small-scale sustainable meat producers to sell directly to consumers using a meat share approach, using constrained optimization techniques to maximize utility for everyone involved. In this post, I’ll walk through some R code that I wrote to demonstrate the technique on a small

I wrote this post months ago but never hit 'Publish'. But, the subject has changed little since then. So, here's to cleaning out the draft folder... R's connections are the heart of data/code/text input and output. Without connections, R would be crippled. Additional connections make R more ... connected with potential data sources and output

I’m helping out some colleagues learn programming from having zero experience with it in any shape or form. It’s quite a daunting task in some senses, because, well, it may not be easy! They are researchers, so they’ll need it for processing data and generating output, and perhaps processing BIG DATA at some point too.

Gompertz Model Visualization # Gomperz growth function gomp <- function(x, a, b, k) a*exp(-b*exp(-k*x)) # Normal model with Gompertz mean function likelihood <- function(weight, age, sigma, a, b, k) { mu <- gomp(age, a, b, k) dnorm(weight, mu, sigma) } # Visualize the model visualize <- function(phi=40, theta=-35) { weight <- seq(0, 250,

I’ve also previously put up a couple of posts about aggregating data in R. In this post, I’m going to be trying some other alternative methods for aggregating the dataset. Before I begin, I’d like to thank Matthew Dowle for highlighting these to me. It’s a bit daunting at first, deciding which method of aggregating data is

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