In which Mo Farah et al show James that he's got a nasty heel-strike
Blog Archives
Gaussian process regression with R
I’m currently working my way through Rasmussen and Williams’s book
Grrr…
I’ve been working through Gelman et al.’s otherwise excellent Bayesian Data Analysis
Sampling for Monte Carlo simulations with R
I've knocked together a quick function for generating efficient Monte Carlo samples. It takes a bit of the legwork out of running Monte Carlo simulations.
Getters and setters in R
When I first started using R, one of the things that attracted me was its claim to be an object-oriented programming (OOP) language. Coming from a Java background, I was used to designing software with OOP concepts like encapsulation and inheritance but, when I turned my hand to R, I quickly...
Positive coefficient regression in R
Ever have a regression model where the coefficients don't make sense? I've been trying to predict electricity and gas consumption from daily activity schedules but a simple linear regression kept saying that demands should go down the more an activity is performed. Fortunately I found the nnls package and show here how you can use it to...
Slopegraphs in R
The internet seems abuzz this week with the "discovery" of a long-lost Edward Tufte plot type: the slopegraph. In this post, I'll show you how to create these elegant compact plots using R and ggplot2.
How to do a quantitative literature review in R
In the early stages of a literature review, you may have hundreds of papers and not know how to even begin sorting through them. In this post, I show you how to perform a two-stage clustering analysis with R so that you can identify the main groups within your data, based on key attributes of each paper.
How to: Multinomial regression models in R
Apples, oranges, pears or bananas? Bus, train, car, or walk? Many choices are made between more than two options, a situation that can be represented by multinomial choice modelling. Here's a quick tutorial on how to do it in R.
How to: Binomial regression models in R
Ever wondered how to predict success or failure as a function of other variables? Here's a quick tutorial on binomial regression in R.
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
