I’m writing a series of posts on various function options of the glmnet function (from the package of the same name), hoping to give more detail and insight beyond R’s documentation. In this post, we will focus on the standardize … Continue reading →

The glmnet function (from the package of the same name) is probably the most used function for fitting the elastic net model in R. (It also fits the lasso and ridge regression, since they are special cases of elastic net.) … Continue reading →

Spatial visualizations really come to life when you have a real map as a background. In R, ggmap is the package that you’ll want to use to get these maps. In what follows, we’ll demonstrate how to use ggmap with … Continue reading →

Principal components (PC) regression is a common dimensionality reduction technique in supervised learning. The R lab for PC regression in James et al.’s Introduction to Statistical Learning is a popular intro for how to perform PC regression in R: it is … Continue reading →

A few posts ago (see here), I noted that there was a group of 7 teams in the English Premier League (EPL) that seem to be a cut above the rest: Arsenal Chelsea Everton Liverpool Manchester City Manchester United Tottenham … Continue reading →

I recently got a hold of table standings for the English Premier League (EPL) for the past 10 years. In this post, I want to explore the question: How similar are the point distributions across seasons? Code for the figures … Continue reading →

When you are plotting many points on one plot, changing the transparency, or alpha, of the points is often a good idea. For example, the plot below plots price vs. carat for each of 53,940 diamonds: We get a mess/mass … Continue reading →

I recently got a hold of team rankings for the English Premier League (EPL) for the last 10 years (data was manually recorded from this Google sheet, available here in .csv format). I thought this would be a good opportunity … Continue reading →

With the FIFA World Cup in my recent memory and the English Premier League (EPL) kicking off this Friday (see here for match schedules), I’ve been thinking a bit about the mathematics/statistics of the beautiful game. In this post, I … Continue reading →

R has a colon operator which makes it really easy to define a sequence of integers. For example, the code 1:10 generates a vector of consisting of the integers from 1 to 10 (inclusive). However, using the colon operator is … Continue reading →

Did you know that you can include math expressions in your text annotations of figures in R? This webpage has an excellent tutorial on how to do so. In essence, you can put your plot label (with some syntax) in … Continue reading →